The limitations of subgroup analyses are well established—false positives due to multiple comparisons, false negatives due to inadequate power, and limited ability to inform individual treatment decisions because patients have multiple characteristics that vary simultaneously. In this article, we apply Bayes’s rule to determine the probability that a positive subgroup analysis is a true positive. From this framework, we derive simple rules to determine when subgroup analyses can be performed as hypothesis testing analyses and thus inform when subgroup analyses should influence how we practice medicine.