Pillar · Free calculator

Personal injury settlement calculator.

Defensible, jurisdiction-tuned settlement value for plaintiff personal-injury cases. Confidence-banded. Sourced. Built for the attorney making the case-selection call at intake — not for the carrier setting reserves on the other side.

See a sample prediction, then run your own.

Below is one case the model has already scored: a low-speed rear-end in Harris County, shown with its 90% confidence band. Enter your own six case facts to get your number. Free, no signup to start.

Run your own case next.

Answer six questions and get a jurisdiction-tuned settlement number with a 90% confidence band. Free to run. The 14-day trial only adds the cited comp set and the demand-letter export.

Enter my case (6 questions, ~60 sec) →

Free · 60 seconds · no signup to start · plaintiff-only by design. The optional 14-day trial is $0 today, then $499/mo, cancel anytime.

This free version runs the same model architecture on the core six inputs. The 14-day trial adds the secondary signals, the cited comp set behind each number, jurisdiction breakouts, and the demand-letter export. Same method, more inputs.

312,000
Jury verdicts and reported settlements in the training data, 2018–2025
92%
Median accuracy on a held-out test set (MdAPE), MVA + PL
50
US jurisdictions covered, stratified jurisdiction folds
90%
Confidence interval on every published number

Held-out test set: 90–92% accuracy (Median Absolute Percentage Error) against actual outcomes, 92% on MVA and 91% on premises liability. The full split, the folds, and the confidence-band derivation are on the methodology page. The number is the headline; the band is the methodology.

How the calculator works

The Predict-Your-Case Calculator runs your inputs through a gradient-boosted regression trained on 312,000 jury verdicts and reported settlements from 2018 forward. It returns a confidence-banded settlement value — a point estimate plus the 90% interval — alongside the comparable-verdict cohort and the jurisdiction tuning that produced the number.

The 30-second flow
Inputs
6 fields
Jurisdiction · case type · severity · liability · specials · PD
Model
XGBoost · 800 trees
312K verdicts · stratified jurisdiction folds
Output
Number + 90% band
5–10 cited comparables · 30 seconds
Same calculator running here is the same model running inside the trial. The trial unlocks the cited cohort, the demand-letter export, and unlimited predictions.

The model is plaintiff-only. The training data, the case-history attributes, and the verdict outcomes are all sourced from plaintiff-side filings, public PACER records, and reported verdict databases. There is no claims-side carrier data in the model, and there never will be. Plaintiff-only is the trust contract; the dataset reflects it.

The output is designed for the intake call. 30 seconds, not two hours. Type the case facts you'd type into a Verdict Search lookup, get a number with a band before the retainer is signed.

Inputs that actually move the number

Six inputs do most of the work. The model handles dozens of secondary signals — judge composition, plaintiff-counsel reputation, per-county settlement medians — internally, but the six fields a plaintiff attorney can supply at intake are:

Inputs ranked by impact on the predicted number
Jurisdiction
0.42
Injury severity
0.31
Liability clarity
0.22
Medical specials
0.16
Case type
0.13
Property damage
0.04
Weights are mean SHAP contributions on the MVA fold. Jurisdiction does ~3× the work of any other input — which is why the "$485K in Harris County, $112K in Miami-Dade" gap below isn't a quirk; it's the model.
  • Jurisdiction. The single largest factor. A low-speed rear-end MVA settles for a median of $485K in Texas · Harris County and a median of $112K in Florida · Miami-Dade. Same fact pattern, different number — because Florida is a no-fault state with capped PIP economics and Harris County juries return materially higher general damages.
  • Liability clarity. Clear liability (rear-impact with admitted fault) multiplies the predicted value against a shared-comparative case at the same severity. Probable liability lands in the middle. The model doesn't pretend a contested case is worth the same as an admitted one.
  • Injury severity. Minor, moderate, severe, catastrophic. The severity ladder is the second-largest factor after jurisdiction. Soft-tissue cases settle at small multiples of medical specials; catastrophic injuries — TBI, paralysis, permanent impairment — settle at 10–14× multiples plus jurisdiction-dependent non-economic damages.
  • Medical specials. The anchor for the damages calculation. The classic "multiple of meds" heuristic is a reasonable first approximation, but the multiplier itself varies by severity, liability, and jurisdiction — which is why a static spreadsheet misses by 30–50% on cases the model lands inside the band.
  • Property damage. A weak signal on settlement value, but a useful one for sanity-checking severity claims. The model uses it as a correction term, not as a primary driver.
  • Case type. MVA versus premises liability. The same medical-specials profile produces materially different settlements across case types — premises cases carry comparative-fault risk almost everywhere, which compresses the upside.

The calculator on this page accepts all six. The full Predict model — available inside the 14-day free trial — adds the secondary signals automatically once a case is loaded into the system.

Why every number ships with a confidence band

The instinct, when building a pricing model for attorneys, is to suppress uncertainty. A clean number is more decisive; a number with a band looks less authoritative. We almost did that. We were talked out of it by attorneys.

Attorneys are trained to evaluate uncertainty. It's the job. A point estimate without a defense is worse than no estimate at all — it forces the attorney to choose between trusting a black box and rejecting the entire tool. A confidence band is the defense. It says: here is what we know, here is the precision of what we know, and here is what would have to be true for the number to move.

The number is the headline. The band is the methodology. Never lead with the range.

The band on every Predict prediction is a 90% confidence interval — meaning 9 out of 10 cases with the same input profile settle inside the published range. If a prediction misses outside the band, we recalibrate the model for that jurisdiction and disclose the recalibration. That's a brand commitment, not a marketing line.

The 90% confidence band · in plain language
5% lower tail 90% inside the band 5% upper tail
9 of 10
cases with the same input profile settle inside the published range
1 of 10
are the long tail — flagged, not hidden. Out-of-band misses trigger recalibration + public disclosure.
The number is the headline. The band is the methodology. Never lead with the range — but never hide it either.

By case type — MVA and premises liability

The two case types Predict is calibrated for cover roughly 70% of plaintiff PI volume by case count. Each has its own modeling considerations:

  • Motor vehicle accidents (MVA). The most predictable category — clear severity gradients, well-documented medical histories, dense jurisdiction-level verdict data. Confidence bands on MVA cases are typically tight (±8–14% at the moderate severity tier). The MVA settlement calculator walks through the case-specific factors and surfaces typical comp ranges.
  • Premises liability (PL). Slower-moving, more comparative-fault exposure, more variation across jurisdictions. Confidence bands run modestly wider (±12–18% at moderate severity). The premises liability settlement calculator handles slip-and-fall, retail premises, and commercial-property cases.

The calculator on this page handles both case types. The two specific calculators add the case-type-specific guidance — what to look for at intake, what the band typically looks like, which jurisdictions have the densest comparable-verdict data.

MVA vs PL · how the two folds differ
Motor vehicle accidents ~ 55% of PI volume
Training cohort198K
Held-out MdAPE92%
Typical band (moderate)± 8–14%
Cohort densityHigh
Premises liability ~ 15% of PI volume
Training cohort72K
Held-out MdAPE91%
Typical band (moderate)± 12–18%
Cohort densityModerate
Together, the two folds cover ~70% of plaintiff PI volume by case count. Wider PL bands are the methodology earning its keep — the model widens uncertainty where the cohort earns it.

Why jurisdiction is the largest single factor

State-level PI economics vary by an order of magnitude. The same fact pattern — a low-speed rear-end MVA with clear liability, moderate cervical strain, $24K in medical specials — settles for a median of $485K in Texas, $352K in Georgia, $305K in California, $112K in Florida (no-fault), and $78K in New York (no-fault). The model trains separate jurisdiction folds for each state and, where data density allows, each county.

Same case · five states · 6× spread
TexasTort · Harris Co.
$485K
GeorgiaTort · Fulton Co.
$352K
CaliforniaTort · Alameda Co.
$305K
FloridaNo-fault · capped PIP
$112K
New YorkNo-fault · serious-injury threshold
$78K
Identical fact pattern: low-speed rear-end MVA, clear liability, moderate cervical strain, $24K medical specials. The only thing that changes is jurisdiction — and the predicted median moves by 6×. A jurisdiction-agnostic model would over-predict no-fault states and under-predict tort jurisdictions; stratified folds prevent that collapse.

For a per-state breakdown of median MVA settlement values, jury-verdict density, and the no-fault versus tort regime, see the state-by-state calculator hub. State pages are calibrated against the local verdict dataset for each jurisdiction.

Predict vs. Verdict Search, settlement-evaluator firms, and gut

Three things compete with Predict in the buyer's head at the decision moment:

Four-way comparison at the decision moment
Predict
$499 / month
30 seconds at intake
Unlimited predictions
5–10 cited comparables · band
Inside the workflow
Status quo
Gut + spreadsheet
"Free" — at $200–350/hr of attorney time
Anchored to PD photo + caller affect
No defense under cross
Breaks at scale
Lookup db
Verdict Search
~ 2 hours per lookup
Retrospective · post-retainer
Library of comps, not a model
$4–8K/yr per seat
Outsourced
Evaluator firms
1–2 weeks per case
~ $1,500 per case
Paralegal-written memo
Not integrated · slow
A 2-case-per-quarter improvement in case selection pays the Predict subscription back in a single settlement. The math is real; the assumption is that the case-selection decision is currently anchored to the wrong signals.
  • Doing nothing — gut + spreadsheet. The largest competitor. The status quo for most solo and small-firm PI attorneys. Predict's claim against gut is that a 2-case-per-quarter improvement in case selection pays the subscription back in a single settlement. The math is real; the underlying assumption is that the case-selection decision is being made on the wrong anchor (property damage and how the caller sounded on the phone) rather than the right one (jurisdiction-tuned, severity-weighted comparable-verdict comp).
  • Verdict Search / Jury Verdict Reporter. Industry-standard lookup databases. Retrospective, manual, slow. A two-hour Verdict Search session at the end of the day produces a comp a week after the retainer is signed. Predict produces a number at intake — when the decision actually gets made.
  • Outsourced settlement-evaluator firms. Paralegal-staffed firms that produce demand-letter valuations on a per-case basis. Slow (one to two weeks), expensive (~$1,500 per case), not integrated into the intake flow. Predict delivers the same valuation in 30 seconds, inside the workflow, included in a $499/month subscription.

Frequently asked questions

How is a personal injury settlement value calculated?

Settlement value is driven by liability clarity, injury severity, medical specials, property damage, plaintiff-counsel reputation, and jurisdiction-specific verdict history. The Predict model trains a gradient-boosted regression on 312,000 jury verdicts and reported settlements, with stratified jurisdiction folds, and produces a confidence-banded prediction for each case.

How accurate is the Predict settlement calculator?

The model holds 90–92% accuracy on a held-out test set for motor vehicle accident and premises liability cases. Accuracy is measured as the Median Absolute Percentage Error (MdAPE) against actual settlement/verdict outcomes. The methodology page documents the test methodology, the held-out split, and the per-jurisdiction calibration. If a prediction misses outside the published confidence band, we recalibrate and disclose.

Why are confidence bands shown with every prediction?

Attorneys are trained to evaluate uncertainty. A number without a defense is worse than no number at all. The confidence band is the methodology — it shows what we know, the precision of what we know, and what would have to be true for the number to move.

Does Predict sell to insurance carriers?

No. Predict is plaintiff-only by design. We will never sell to insurance carriers, defense firms, or any defense-side claims operation. The proprietary case-outcome dataset flows in one direction: toward the attorneys fighting for plaintiffs.

What case types does the calculator support?

Motor vehicle accident (MVA) and premises liability (PL) at launch — the two case types where the model is calibrated to 90%+ accuracy. Medical malpractice, mass tort, and workers compensation are out of scope for the current product.

Is the calculator really free?

Yes. The public calculator on this page is free and requires no signup. It runs the demo model — the same architecture as the full Predict model, but with fewer secondary signals. The full model — case-history sources, demand-letter integration, jurisdiction breakouts, and the in-workflow case-load view — runs inside the 14-day free trial. The trial requires no credit card at signup.

Deeper into the topic

Specific calculators and the methodology behind them.