This study evaluated the classification accuracy of a second grade oral reading fluency curriculum‐based measure (R‐CBM) in predicting third grade state test performance. It also compared the long‐term classification accuracy of local and publisher‐recommended R‐CBM cut scores. Participants were 266 students who were divided into a calibration sample (n = 170) and two cross‐validation samples (n = 46; n = 50), respectively. Using calibration sample data, local fall, winter, and spring R‐CBM cut scores for predicting students’ state test performance were developed using three methods: discriminant analysis (DA), logistic regression (LR), and receiver operating characteristic curve analysis (ROC). The classification accuracy of local and publisher‐recommended cut scores was evaluated across subsamples. Only DA and ROC produced cut scores that maintained adequate sensitivity (≥.70) across cohorts; however, LR and publisher‐recommended scores had higher levels of specificity and overall correct classification. Implications for developing local cut scores are discussed.