Genetic epidemiology is an emerging field with diverse interests, one that represents an important interaction between the two parent disciplines: genetics and epidemiology. Segregation analysis was originally designed to test whether or not an observed mixture of phenotypes among offspring is compatible with Mendelian inheritance. Over the years, segregation analysis has broadened to encompass, but the ultimate goal is the same: to test for compatibility with Mendelian expectations by estimating parameters of a given model of inheritance. Segregation analysis tests explicit models of inheritance on family data. The analytic strategy relies heavily on fitting genetic models, along with a few arbitrary nongenetic models, and selecting the model that best explains the data. While showing an adequate fit to a genetic model of inheritance in a single data set does not constitute proof that a trait or disease is in truth under genetic control, it may be considered strong statistical evidence. Even though segregation analysis has its limitations, it remains a powerful tool for identifying genetic mechanisms that may control traits associated with disease or contribute to disease risk.