The Kaplan–Meier estimator, also known as the product limit estimator, is a non-parametric statistic used to estimate the survival function from lifetime data. In medical research, it is often used to measure the fraction of patients living for a certain amount of time after treatment. In other fields, Kaplan–Meier estimators may be used to measure the length of time people remain unemployed after a job loss, the time-to-failure of machine parts, or how long fleshy fruits remain on plants before they are removed by frugivores. The estimator is named after Edward L. Kaplan and Paul Meier, who each submitted similar manuscripts to the Journal of the American Statistical Association. The journal editor, John Tukey, convinced them to combine their work into one paper, which has been cited more than 61,800 times since its publication in 1958.

The estimator of the survival function ${\displaystyle S(t)}$ (the probability that life is longer than ${\displaystyle t}$) is given by:

${\displaystyle {\widehat {S}}(t)=\prod \limits _{i:\ t_{i}\leq t}\left(1-{\frac {d_{i}}{n_{i}}}\right),}$

with ${\displaystyle t_{i}}$ a time when at least one event happened, d_i the number of events (e.g., deaths) that happened at time ${\displaystyle t_{i}}$, and ${\displaystyle n_{i}}$ the individuals known to have survived (have not yet had an event or been censored) up to time ${\displaystyle t_{i}}$.