Early identification of students needing additional support is a foundational component of Multi-Tiered Systems of Support (MTSS). Due to the resource-intensive nature of implementing MTSS, it is critical that universal screening procedures are maximally accurate and efficient. The purpose of this study was to compare the classification accuracy of aimswebPlus reading scores to the Benchmark Assessment System scores. We used data from a mid-size city in Texas to retrospectively compare the classification accuracy between fall aimswebPlus reading composites to the Benchmark Assessment System scores when predicting student performance on the statewide reading test. When classification decisions were made based on the vendor-recommended cut-scores, both measures were insufficiently sensitive for screening in MTSS. Following aimswebPlus' recommended method for establishing local-cut scores improved the sensitivity of decisions, but the specificity values were well below minimally acceptable levels. Limitations, directions for future research, and implications for practice are discussed.