Hypotheses. Extending previous research, Big Data seeks to identify factors that relate LD to recidivism, frequency of re-offending and re-arrest, and the time to post-involvement recidivism. We hypothesize that (a) overall recidivism rates (i.e., regardless of the specific type of offense) will be higher among JJ-involved youth with severe LD (operationalization based on standardized achievement tests and special education status) than in youth without LD; (b) youth with severe LD will show more incidents of school-related problems after their first involvement (e.g., attendance problems, disciplinary incidents such as in-school and out-of-school suspensions and expulsions) than youth without LD; (c) youth with severe LD who had school-related problems prior to their first JJ involvement will be at higher risk of recidivism than youth without LD; (d) lower levels of reading achievement will be associated with shorter periods of time to repeated offending; and (e) participation in the intervention will significantly decrease recidivism risk compared to other youth with severe LD who did not participate in the intervention.