Answering a hard question by trying many random possibilities and looking at what happens. If you cannot calculate the odds directly, simulate the situation thousands of times and count. It is the workhorse behind risk modelling, game-playing systems and a great deal of statistics.
Technical view
Estimating expectations by sampling, with error decreasing as the inverse square root of sample count regardless of dimension, which is why it beats grid methods in high dimensions. Variants include importance sampling and Markov chain Monte Carlo for sampling from distributions known only up to a constant. Monte Carlo tree search underpinned the game-playing systems of the 2010s and reappears in reasoning models that search over candidate solutions.
Related
Part of AI Terminology Index, section: Maths and Statistics.