Risk assessments that include dynamic risk factors are increasingly being utilized within the youth justice system to predict a young person’s likelihood to reoffend, to assist with case management, and to better inform intervention services. However, most studies to date have relied solely on single-wave cross-sectional research designs that essentially treat dynamic risk factors as static. Thus, it is unclear whether and how putative dynamic risk factors change over time, a question that has significant implications for assessment and case management policy and practice. Using a widely used and validated risk assessment and case management instrument (the Youth Level of Service/Case Management Inventory), the purpose of the present study was to examine whether the dynamic risk factors outlined in the Risk-Need-Responsivity (RNR) model do in fact change over time and, if so, to investigate the effect of youth-specific predictors on these changes. Two hundred youth offenders were tracked from their first risk assessment conducted at probation to their transition out of the youth justice system. Results from generalized linear mixed modelling (GLMM) and latent class growth modelling (LCGM) analyses indicated that most dynamic risk domain scores increased over time, but that there was significant individual variation among youth at initial status and in the rate of change. Even when controlling for youth-specific factors, youth who were lower risk at the time of initial assessment increased in risk at a greater rate than higher-risk youth. Results have implications for the RNR framework, for improving the accuracy of risk assessments, and for informing treatment implementation.