Higher education institutions have prioritized supporting undecided students with their major and career decisions for decades. This study used a U.S. public research-focused university's large-scale institutional data set and undecided student's retention and graduation rate predictors to demonstrate how to couple student and institutional data with predictive analytics to understand the different demographics, academic characteristics, and the number of major changes between undecided and decided students. This study helps practitioners take the first step in using data analytics to inform decision-making in academic advising and supporting undecided students' academic success.