**Link**: Bayesian statistics Bayes’ theorem

**Prior probability** is your initial guess or belief. e.g. the prior probability of flip a coin is 50%.

**Posterior probability** is your adjusted belief after considering new information. E.g. the posterior probability of flipping a coin 1 is 100% after getting a head.

The difference is that posterior probability reflects the new information and takes this into account.