Bayes' Theorem

The probability that belief A is true, given new evidence B is equal to the probability of B given A times the probability of A (regardless of B) divided by the probability of B (regardless of A).

In Bayes’ Theorem, the probability of something occurring is based on probabilities of other parameters of the problem. Put simply, using the theorem builds on prior knowledge of the problem domain to update a prediction. This became very popular because, in the real world, there is much uncertainty and Bayes Theorem provides a way of modeling that uncertainty through probability (e.g. machine learning).