Abstract: Military veterans are at increased risk for suicide compared to civilians. Suicide risk may be influenced by psychosocial risk and protective factors, including sense of purpose and social connection, depression, posttraumatic stress disorder, and moral injury. This study applied latent profile analysis (LPA) to investigate heterogeneity in these factors in a large community sample of veterans (n = 3,185). Following LPA model identification, latent profiles were modeled as predictors with suicide risk as the outcome. A multinomial logistic regression model was then used to investigate associations between demographic characteristics, military-specific variables like Veterans Health Administration health and mental health care utilization, and latent profile membership. LPA results supported a five-profile solution to the data. The highest risk profile had 5 times the odds of exceeding a suicide risk scale cutoff compared to the normative profile. Age, education, marital status, deployments, and Veterans Health Administration service use variables were significantly linked with latent profile membership, with implications for suicide risk assessment, prevention, and intervention in veteran populations.