Universal screening for social, emotional, and behavioral risk is an important method for identifying students in need of additional or targeted support (Eklund and Dowdy in School Mental Health 6:40–49, 2014). Research is needed to explore how potential bias may be implicated in universal screening. We investigated student demographics as predictors of being placed at risk via a teacher-report measure: the Social, Academic, and Emotional Behavior Risk Screener as reported by Kilgus et al. (in: Theodore J. Christ et al. (eds) Social, academic, and emotional behavior risk screener (SAEBRS), 2014). Results indicated student demographics, including sex, special education status, free/reduced price lunch status, and identification as a student of color, were statistically significant predictors across multiple SAEBRS risk placements. The predictive power of student demographics was meaningful when evaluated independently (i.e., when each characteristic was considered separately with each risk placement) as well as when evaluated relatively or dependently (i.e., when all characteristics were taken together as a set to predict each risk placement). We discuss findings in the context of implications for implementation of universal behavioral screening amidst potential bias and serving students with identified levels of social, emotional, and behavioral risk.