The current study used factor mixture modeling to identify heterogeneity (i.e., latent classes) in 2 well-supported models of posttraumatic stress disorder's (PTSD) factor structure. Data were analyzed from a clinical sample of 405 Canadian veterans evaluated for PTSD. Results were consistent with our hypotheses. Each PTSD factor model was best represented by 2 latent classes of participants, differing with respect to PTSD symptom severity. Furthermore, classes were most strongly distinguished by factor scores related to emotional numbing or dysphoria. For both factor models, class membership was significantly predicted by age and depression diagnosis. Implications of these findings are discussed.