The current study examined the validity of curriculum-based measures (CBM) in mathematics computation (M-COMP) and oral reading fluency (R-CBM) in predicting spring mathematics and reading performance level and performance risk (>1 SD below the national mean) among students classified as English Learners (ELs). Additionally, the current study assessed the incremental predictive value of English language proficiency (ELP) beyond CBM performance. The results indicated that ELP explains a significant portion of variability above M-COMP and R-CBM and increases the accuracy of predicting at-risk performance status on spring measures of mathematics and reading. The findings highlight the challenges of assessing the predictive accuracy of M-COMP and R-CBM among students classified as ELs, as well as the extent to which comprehensive measures of ELP account for variance in both performance level and at-risk status beyond CBMs. The implications for school data-based decision-making for language-minoritized students and directions for future research are discussed.