For students with persistent reading difficulties, research suggests one of the most effective ways to intensify interventions is to individualize instruction through use of performance data--a process known as data-based decision making (DBDM). This article reports a synthesis and meta-analysis of studies of reading interventions containing DBDM for struggling readers, as well as the characteristics and procedures that support the efficacy of these interventions. A systematic search of peer-reviewed literature published between 1975 and 2017 was conducted, resulting in 15 studies of reading interventions that incorporated DBDM for struggling readers in Grades K-12. A comparison of students who received reading interventions with DBDM with those in business-as-usual (BAU) comparison groups yielded a weighted mean effect of g = .24, 95% confidence interval (CI) = [0.01 to 0.46]. A subset of six studies that compared students receiving similar reading interventions with and without DBDM yielded a weighted mean effect of g = 0.27, 95% CI = [0.07, 0.47]. Implications for DBDM in reading interventions for struggling readers and areas for future research are described. In particular, experimental investigation is necessary to establish DBDM as an evidence-based practice for struggling readers.