Stochastic medical informatics is an approach to reasoning about clinical phenomena that manages the inherent uncertainty and complexity through statistical methods such as random sampling from probability distributions. The representation of information, such as the possible clinical outcomes for patients, and reasoning about it can be highly complex and computationally overwhelming. Simplifying assumptions must be made to manage such information to make useful predictions and rational decisions. Observations of patient populations and possible events can often be described conveniently in terms of conditional probability distributions. Such statistics can then be assembled into rational, decision-analytic or simulation models that can then be subjected to systematic analyses for making predictions and policy decisions.