How we calculate MOT risk & reliability
We turn the UK's public MOT record into clear, comparable measures of reliability and risk. This page explains, in plain English, where the data comes from, how each figure is worked out, and — importantly — what it can and can't tell you.
Where the data comes from
Every figure on this site is derived from the UK's official MOT test data, published by the Driver & Vehicle Standards Agency (DVSA). It covers tens of millions of vehicles and their MOT test results — pass/fail outcomes, recorded mileage and the advisories and defects noted at each test. We aggregate this into make- and model-level statistics and refresh it periodically, so figures reflect the data as at our most recent update.
How we measure model reliability
A model's MOT pass rate is the share of its completed tests that passed — that is, passes ÷ (passes + fails). We deliberately exclude test records with an outcome that isn't a clear pass or fail (for example abandoned tests), so they can't distort the rate. Where a model has too few completed tests to be meaningful we say so, rather than show a misleading number.
Our reliability league tables only rank models with a substantial sample, so a handful of tests on a rare model can't top or bottom the chart. Reliability also depends on a car's age, mileage and how it's been looked after — the pass rate is one strong signal, not the whole story.
How the MOT risk score works
The risk score on a vehicle report is a 0–100 indicator (higher = more risk) that blends several signals from that specific car's MOT history against how its model typically performs:
- Model & age baseline — how often this model fails at roughly this age.
- The car's own pass/fail record — smoothed toward the model average so a single bad year on a short history isn't over-weighted.
- Recent & recurring advisories — issues flagged lately, and faults that keep coming back.
- Mileage — relative to typical for the model, including a check for odometer readings that go backwards between tests (a possible discrepancy).
- Safety history — any dangerous or major defects recorded.
We also show a confidence level: a car with only one or two tests gives us less to go on, so its score is pulled toward the model average and labelled lower-confidence.
How we predict the chance of failing the next MOT
Alongside the risk score we show an estimated chance of failing the next MOT. This comes from a statistical model (logistic regression) trained on millions of historic MOT tests. For each past test the model learned the relationship between the outcome and factors known beforehand — the car's age, recorded mileage and mileage per year, its prior pass/fail record, how the model generally performs, fuel type, engine size and the time of year.
We validate it on a held-out set of vehicles the model never saw during training and measure its ability to separate passes from fails (the “AUC”). The output is a probability, shown as a percentage — an informed estimate of likelihood, not a guarantee of what will happen.
What this is — and isn't
Everything here is indicative and based on MOT data only. It is general information, not advice, and not a recommendation to buy or avoid any vehicle. It is not a mechanical inspection, a valuation, or a full vehicle-history check (finance, write-off, theft, plate changes). MOT records can be incomplete or contain data-entry errors, and a past result doesn't dictate a future one.
Before making a decision about a car, always view it in person, check its service history, and consider an independent professional inspection and a full vehicle-history check. If you spot something that looks wrong in our data, please get in touch.
Source: DVSA MOT testing data. VehicleStats is independent and not affiliated with the DVSA or gov.uk. See also our car & MOT guides.