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This study uses regression with LASSO selected covariates to examine the relationship between a student being suspended in high school and their likelihood of applying to college, being admitted to college, and being offered financial aid in college. The use of LASSO, a machine learning technique for identifying relevant covariates, contributes to the methodological rigor of the analysis. Findings suggest that students who are suspended are less likely to apply, be accepted, or receive an offer of financial aid. However, only the lower likelihood of applying to college is statistically significant after controlling for covariates. The implications for school discipline and college admissions are discussed.