Monte Carlo simulation is a computerized mathematical technique used to analyze risk. Monte Carlo simulation performs risk analysis by building computer models of possible results by substituting a range of values—a probability distribution—for any factor that has uncertainty. It then calculates results over and over, each time using a diﬀerent set of random values from the speciﬁed probability function for each factor. It furnishes the decision-maker with a range of possible outcomes and the probability they will occur for any action—it shows how variations in important factors interact. It also shows the extreme possibilities. Results show not only what could happen, but how likely each outcome is. Probability distributions are a much more realistic way of describing uncertainty in variables than deterministic or “single-point estimate” analysis.