Detecting mental health concerns in youth accurately and promptly may prevent poor school outcomes, long-term mental illness, and adverse lifelong outcomes. Practitioners often use universal behavioral risk screeners to identify students at-risk on indicators related to mental health concerns. However, research is needed to inform the stability of risk identification scores across the academic year. Using a sample of N = 1496 elementary and middle school-aged students, latent class analysis and latent transition analysis were employed to identify and characterize the risk classes and the stability of latent classes of student risk longitudinally across one school year (i.e., fall, winter, and spring). The screener of interest within this study was the Social, Academic, and Emotional Behavior Risk Screener--Student Rating Scale (SAEBRS-SRS). Results revealed three distinct risk classes (low, moderate, and high risk) that remained stable across screening periods. Future directions and implications for practice are discussed.