Abstract:The transition out of military service and into civilian life represents a considerable challenge for many military veterans. In this study we used mixture growth modeling and random forest analysis to examine predictors of adjustment to civilian life among recently released Canadian veterans (unweighted N=455, weighted N=11,100, weighted Mage = 44.58, SD=11.01). We used data from a national, longitudinal survey of Canadian military veterans, and examined 36 potential predictors of adjustment that included demographics, military characteristics/experiences, health behaviours, variables related to accessing care, social factors, psychological constructs, and physical health indicators. The results of mixture growth modelling revealed three distinct classes of adjustment following military release. Random forest analysis subsequently identified the most important predictors of adjustment (in order of importance), including life satisfaction, a sense of mastery, mental health, satisfaction with participants’ main activity (e.g., employed, retired), financial satisfaction, social support, general health, body mass index, age, and income. These predictors were used to examine differences among the latent classes. Our results revealed noteworthy differences between distinct classes of veterans, with regard to these predictor variables, the findings of which have the potential to inform targeted supports for veterans following release from the military.