Monte Carlo Simulation

Statistical technique using random sampling to model uncertainty and estimate outcome probabilities.

A Monte Carlo simulation in risk assessment is a statistical technique that uses repeated random sampling and probability distributions to model the uncertainty of complex systems or processes, generating thousands of possible scenarios and estimating the likelihood of various outcomes. Instead of relying on a single risk score or fixed assumptions, this method constructs a full range of potential results by assigning probability distributions to key variables, running simulations, and analyzing the resulting distribution of possible outcomes. This allows decision-makers to better understand and quantify risks, evaluate the probability of different scenarios, and make more informed choices under uncertainty.