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The purpose of this quantitative study was to find predictors of student success. Using a predictive correlational design, the intent of the study was to find the relationships between the dichotomous dependent variable with the categories, degree recipients and non-degree recipients, and the independent variables, student characteristics and risk factors. The conceptual framework for this study was Astin's Input-Environment-Outcome (I-E-O) model which addresses the complexities of research in higher education by highlighting the interdependence between inputs, environments, and outputs. The use of a predictive design allowed the researcher to find the likelihood of a relationship between outcomes by using the independent variables as predictors. To address the research questions descriptive statistics, bivariate cross tabulations, and binary logistic regression were conducted. The descriptive statistics were reported from the participants' responses and the percentage of the total response. The bivariate cross tabulations measured the relationship between the expected and observed counts for the two categories.