The growth in the availability of longitudinal data—data collected over time on the same individuals—as part of program evaluations has opened up exciting possibilities for evaluators to ask more nuanced questions about how individuals’ outcomes change over time. However, in order to leverage longitudinal data to glean these important insights, evaluators responsible for analyzing longitudinal data face a new set of concepts and analytic techniques that may not be part of their current methodological tool kit. In this article, I provide an applied introduction to one method of longitudinal data analysis known as multilevel growth modeling. I ground the introductory concepts and illustrate the method of multilevel growth modeling in the context of a well-known longitudinal evaluation of an early childhood care program, the Carolina Abecedarian Project.