Data-based individualization (DBI) is a systematic approach to intensifying and individualizing interventions for students who require more support. Diagnostic data represent the third step in the DBI process. When progress monitoring data indicate that a student is not making adequate progress in an intervention, educators use diagnostic data to learn more about the student's strengths and areas of need. Based on diagnostic data, educators develop a hypothesis about why the student has not yet responded to the intervention. The hypothesis is a proposed explanation for the student's lack of progress and serves as a starting point for intervention adaptation (Step 4 of DBI). Educators often have an overall sense of student needs, but it is important for them to use data to develop a hypothesis for why the student has not yet made sufficient progress. Diagnostic data can help make this process more systematic by providing the information necessary to develop a hypothesis that is accurate, specific, and actionable. In this brief, the authors offer recommendations to support educators to efficiently collect, analyze, and use diagnostic data within DBI. Throughout this brief, the authors focus on informal diagnostic data sources (e.g., student work samples, classroom observations) that are easier to use and require less training than formal, standardized diagnostic measures. However, in some cases, formal diagnostic assessment data may be necessary to gather more in-depth information about students' needs. In addition, although the authors include some information about diagnostic assessment for behavioral needs, they focus primarily on academic diagnostic assessment.