Early intervention is a method institutions use to identify and support students who are having academic difficulty and might be designated as "at-risk", or more likely to leave an institution (Villano et al., 2018). Institutions often adopt early alert systems to support early intervention efforts and student retention (Barefoot et al., 2012; Fletcher, 2012; Simons, 2011); however, data supporting their effectiveness are limited. While past studies have examined early intervention effectiveness in individual classrooms or with specific student populations, few studies reviewed for this study have examined broad scale interventions implemented at key time points in the semester and have high faculty participation. Therefore, the intent of this study was to examine the efficacy of early intervention as a predictor of retention using an early alert system for an undergraduate student population with a focus on historically underserved student populations at a mid-sized public university. Specifically, academic progress check data collected at two timepoints each semester and student engagement with early intervention efforts for most an institution's undergraduate population within an early alert system were studied. Results of blocked logistic regression analyses showed academic progress data in the form of deficiency percentage was consistently highly significant (p < 0.001) across all models, indicating it may be a useful marker to identify students in need of early intervention support. While the scope of this study was necessarily limited to one institution's early intervention system and processes, the guiding framework, and subsequent implications of findings from this study could help institutions in assessing their early intervention systems as retention tools. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]