Alongside academic learning, there is increasing recognition that educational systems must also cater to students’ wellbeing. This study examines the key factors that predict adolescent students’ subjective wellbeing, indexed by life satisfaction, positive afect, and negative afect. Data from 522,836 secondary school students from 71 countries/regions across eight diferent cultural contexts were analyzed. Underpinned by Bronfenbrenner’s bioecological theory, both machine learning (i.e., light gradientboosting machine) and conventional statistics (i.e., hierarchical linear modeling) were used to examine the roles of person, process, and context factors. Among the multiple predictors examined, school belonging and sense of meaning emerged as the common predictors of the various wellbeing dimensions. Diferent wellbeing dimensions also had distinct predictors. Life satisfaction was best predicted by a sense of meaning, school belonging, parental support, fear of failure, and GDP per capita. Positive afect was most strongly predicted by resilience, sense of meaning, school belonging, parental support, and GDP per capita. Negative afect was most strongly predicted by fear of failure, gender, being bullied, school belonging, and sense of meaning. There was a remarkable level of crosscultural similarity in terms of the top predictors of wellbeing across the globe. Theoretical and practical implications are discussed.