Purpose: Adolescents' mental well-being has become a growing public health concern. Adolescents' daily lives and their engagement in risks have changed dramatically in the course of the 21st Results: Seven clusters of risk were identified: substance use and early sex, low social support, insufficient nutrition, bullying, sugary foods and drinks, physical health risk, and problematic social media use (SMU). Low social support and SMU were the strongest predictors of low life satisfaction (odds ratios ¼ 2.167 and 1.330, respectively) and psychosomatic complaints (odds ratio ¼ 1.687 and 1.386, respectively). Few gender differences in predictors were found. Exposure to bullying was somewhat more associated with psychosomatic complaints for girls, whereas physical health risk was associated with reduced relative odds of low life satisfaction among boys. Split-sample validation and out-of-sample prediction confirmed the robustness of the results. Conclusions: The results highlight the importance of contemporary clusters of risk, such as low social support and SMU in the mental well-being of young people and the need to focus on these as targets for prevention. We propose that future studies should use composite risk measures that take into account both risk behaviors and risk factors to explain adolescents' mental well-being. century, leading to a need to update traditional models of risk to include new exposures and behaviors. To date, studies have examined the relationship between (mainly traditional) risk behaviors and adolescent mental well-being or looked at risk factors that jeopardize mental wellbeing such as lack of social support but have not combined them together to highlight the most significant risks for adolescent mental well-being today. The present study included new and traditional risk behaviors and risk factors, robustly derived an empirically based model of clusters of risk, and examined the relative association of these clusters to adolescent mental well-being. Methods: Data from the 2017e2018 Health Behaviours in School-aged Children study were used. The sample included 32,884 adolescents (51.7% girls) aged 15 years from 37 countries and regions. The principal component analysis was used to determine the existence of clusters of risk, using 21 items related to adolescent mental well-being that included both risk behaviors (e.g., substance use) and risk factors (e.g., peer support). Analysis was conducted in both a randomly split training and test set and in gender separate models. Mixed-effects logistic regressions examined the association between clusters of risk and mental well-being indices (low life satisfaction and psychosomatic complaints).