Theoretical models of addiction suggest that a substance use disorder represents an imbalance between hypersensitive motivational processes and deficient regulatory executive functions. Working-memory (a central executive function) may be a powerful predictor of the course of drug use and drug-related problems. Goal of the current functional magnetic resonance imaging study was to assess the predictive power of working-memory network function for future cannabis use and cannabis-related problem severity in heavy cannabis users. Tensor independent component analysis was used to investigate differences in working-memory network function between 32 heavy cannabis users and 41 nonusing controls during an N-back working-memory task. In addition, associations were examined between working-memory network function and cannabis use and problem severity at baseline and at 6-month follow-up. Behavioral performance and working-memory network function did not significantly differ between heavy cannabis users and controls. However, among heavy cannabis users, individual differences in working-memory network response had an independent effect on change in weekly cannabis use 6 months later (ΔR2 = 0.11, P = 0.006, f2 = 0.37) beyond baseline cannabis use (ΔR2 = 0.41) and a behavioral measure of approach bias (ΔR2 = 0.18): a stronger network response during the N-back task was related to an increase in weekly cannabis use. These findings imply that heavy cannabis users requiring greater effort to accurately complete an N-back working-memory task have a higher probability of escalating cannabis use. Working-memory network function may be a biomarker for the prediction of course and treatment outcome in cannabis users.