The Big Data component seeks to address three objectives: (1) to conduct big data analytics and data mining to quantify/qualify the complexities of severe LD among juvenile justice (JJ)-involved youth using statistical methods applied to big datasets that capture multiple indicators (i.e., offending and educational outcomes) cross-sectionally (for one-time offenders) and longitudinally (for repeat offenders); (2) to utilize big data analytics to identify a group of youth with severe LD who will serve as a comparison group for individuals participating in a reading intervention; and (3) to evaluate the findings from the first two objectives based on the statistical assumptions underlying the models applicable to the big data at hand.