Bayes’ Rule is a simple way of calculating conditional probabilities. Although a great deal has been written about the relevance of Bayes’ Rule in clinical settings, it is difficult to find a single article that is both mathematically comprehensive and easily accessible to students and professionals with clinical backgrounds. This article tries to fill that void, by laying out the nature and implications of Bayes’ Rule in a way that requires little or no background in probability theory. It builds on Meehl & Rosen’s classic (1955) paper, Antecedent probability and the efficiency of psychometric signs, patterns, or cutting scores, by laying out algebraic proofs that they simply allude to, and by providing extremely simple and intuitively accessible examples of the concepts that they simply assumed their reader understood.