CAT Rank Predictor

Your marks are converted to a percentile — the share of candidates who scored below you — and the percentile is then multiplied by the number of candidates who actually sat the exam to give a rank. Because rank is heavy-tailed, this predictor interpolates in log space over the published marks-vs-percentile anchors rather than assuming a straight line, which is what makes the top 1% accurate.

Around 100.00 percentile, which works out to roughly All-India rank 1 in a field of about 3,00,000. Reserved-category ranks are considerably better at the same marks — use the category selector above to see yours.

Yes. Alongside the common rank list, CAT publishes a separate rank list for each category, and the same marks give a much better category rank than All-India rank. Reserved-category candidates are under-represented at the very top of the merit list and converge to their population share further down, so the gap between the two numbers narrows as your rank gets deeper — this predictor models that rather than applying a flat percentage.

CAT sets its bar by percentile rather than by a fixed mark: the General requirement is the 90th percentile. The mark that lands on it changes every year.

It reproduces published marks-to-rank pairs closely where official tables exist — the NEET check reproduces NTA's own percentile column to within 0.001 percentile points. Accuracy is lower for exams that never publish a rank table, where position is modelled from the cutoff instead. Every prediction shows which of the two it used and how confident it is.