This post is one in a series highlighting MDRC's methodological work. Contributors discuss the refinement and practical use of research methods being employed across the organization. Across policy domains, practitioners and researchers are benefiting from a trend of greater access to both more detailed and frequent data and the increased computing power needed to work with large, longitudinal data sets. There is growing interest in using such data as a case management tool, to better understand patterns of behavior, better manage caseload dynamics, and better target individuals for interventions. In particular, predictive analytics--which has long been used in business and marketing research--is gaining currency as a way for social service providers to identify individuals who are at risk of adverse outcomes. MDRC models the experiences of individuals whose outcomes are known in order to predict outcomes for others. MDRC is using predictive analytics to estimate an individual's likelihood of achieving or not achieving key outcomes (such as completing a program milestone, finding employment, or reading at a proficient level).