This study uses a logistic regression model to analyze survey data (n = 341) and predict factors influencing online course success for underserved and academically at-risk undergraduate students at a small, broad access, four-year, public Midwestern university. Three blocks of predictor variables, demographic (first generation, low income, minority status), educational (academic level, prior online experience, online vs. face-to-face major, transfer status, college cumulative GPA), and personal characteristics (self-regulation, Technological Efficacy), were used to explain student success in online courses. Low income, although initially significant, was not a significant predictor in the final model. College cumulative GPA remained a statistically significant predictor of online course success in every block of the regression analysis. Prior online experience and self-regulation were not significant predictors, although the overall model was significant. Controlling for all explanatory variables, college cumulative GPA and Technological Efficacy were found to be the most significant predictors of online course success in the f inal model. With increasing prevalence and popularity of online courses, it is crucial for universities catering to a larger proportion of underserved and academically at-risk students to identify the specific learner characteristics that lead to successful online course completion.