The societal demand for graduates with expertise in Science, Technology, Engineering, and Mathematics (STEM) stands in contrast with prevalent issues of diminished interest among high school students in STEM subjects and low completion rates in STEM academic programs. In the Flemish educational context, heterogeneity in STEM preparedness of incoming students, caused by open admission to higher education (HE) and lack of centralized exams at the end of secondary education (SE), contributes to low completion rates. Pre-enrollment, low-stakes positioning tests aim to inform students of their preparedness. This is an in-depth study of the predictive validity for first-year academic achievement in STEM of these tests. We used data from three academic years, four universities, and six study programs (n = 1973). Using nested linear and logistic regression analyses, we found incremental predictive validity of positioning tests over SE outcomes, and learning and study strategies, especially of the mathematics problems on the tests. Furthermore, we found no evidence for differences in predictive validity between relevant sub-populations (related HE programs, or different SE programs). Finally, we introduced utility functions to determine optimal cut-offs for positioning test scores.