The purpose of this study was to determine if a freshman introductory course (Foundations of Kinesiology) performance is a predictor of academic success for Kinesiology undergraduates. This study was designed to develop a statistical model for determining a Kinesiology student's academic potential. Modeling is a powerful statistical technique; however, few studies have utilized statistical techniques to assess academic success for Kinesiology students. Modeling allows universities to identify academically at-risk students. The Institutional Review Board for the Protection of Human Subjects approved the study prior to data collection. The study was retrospective in nature. The first step was to obtain class lists (N = 889) for students enrolled in Foundations of Kinesiology taught by the same faculty member for eight years. The second step was to obtain graduation status, grade point averages (GPA's), standardized test scores, and points (POINTS) earned in Foundations of Kinesiology for all students in the study. Multiple and logistic regression analysis were utilized to determine predictors of academic success. Alpha was set at the .05 level. Multiple regression analysis was used to determine which variables were significant predictors of grade point average. Each standardized test score and POINTS scored in Foundations of Kinesiology were entered into the full regression model. Regression analysis revealed that POINTS (p = .0001) obtained in Foundations of Kinesiology and scores from a state-wide standardized Math test (MATH) (p = .0009) were significant predictors of GPA. Based upon these results, the following accurate model (SEE = 0.47, R = .74) was derived: GPA = (Points * 0.0058) + (MATH * 0.0076) - 1.1067. Standardized regression weights revealed POINTS from the Foundations of Kinesiology course was the best predictor of GPA. The MATH score accounted for an additional 8% of the GPA variance. ACT and SAT scores were not significant (p > .05) predictors of GPA. The correlation coefficient (r = .669) between POINTS earned in Foundations of Kinesiology and GPA was higher than correlation coefficients from all other standardized test scores and GPA. Logistic regression was then utilized to determine if graduation could be predicted from performance in Foundations of Kinesiology. Students (n = 565) enrolled in Foundations of Kinesiology prior to 1998 were utilized in this analysis. The derived logistic regression model accurately predicted graduation in 68% of the students. Results of this study revealed Foundations of Kinesiology class Points and MATH scores were statistically significant predictors of academic success for Kinesiology students. Keyword(s): assessment, college level issues, student issues