Reading proficiency is fundamental to school success. However, up to 50% of students with reading disabilities are not making adequate progress. Students who demonstrate persistent and severe reading difficulties require increasingly intensive instruction individualized to meet their instructional needs Individualizing instruction with student-level data--a process known as "data-based decision making" (DBDM)--is a recommended practice to intensify intervention for inadequate responders. DBDM is designed to address persistent academic difficulties. Interventions are implemented with greater frequency and duration than typical services, which requires teachers to have adequate knowledge and skills to (a) implement multiple evidence-based interventions to address significant learning needs and (b) use ongoing progress-monitoring data to estimate students' response to intervention programs and to determine when adjustments are needed. Many teachers report a lack of training focusing on using the data that they are already collecting to make instructional decisions; for this reason, it is no surprise that many teachers report that they are not confident in the process of collecting and interpreting data. As such, this step of the DBDM process--progress monitoring--is the focus of the present article. This article presents the following four steps teachers can follow to effectively interpret data and make instructional decisions: (1) select a tool for progress monitoring and administer baseline assessments; (2) determine the frequency of progress monitoring; (3) set a student outcome goal; (4) graph and analyze student data to make instructional decisions.