Importance: Identifying quality-of-life (QoL) subgroups can optimize occupational therapy interventions for stroke survivors. Objective: To identify clusters among stroke survivors on the basis of perceived QoL using latent profile analysis (LPA). Design:Cross-sectional study using LPA to classify QoL levels among stroke survivors and multinomial logistic regression to identify predictors. Setting: Hospital and university clinic. Participants: A total of 696 adult stroke survivors age 18 yr or older. Eligible participants were literate and had a Mini-Mental State Examination score of 23 or higher, excluding those with speech disorders or additional chronic neurological, psychiatric, or cognitive conditions. Outcomes and Measures: The participants were evaluated with the Stroke Impact Scale (SIS), Barthel Index, and the Impact on Participation and Autonomy Questionnaire (IPA). LPA was applied to the SIS data. Results: Three latent classes were identified: high QoL (n = 232), moderate QoL (n = 322), and low QoL (n = 142). Participants in Class 2 (high QoL) demonstrated higher functional outcomes, whereas those in Class 3 (low QoL) displayed the lowest scores across all scales. Predictors of class membership included age, gender, social relationships, and education level. Conclusions and Relevance: LPA effectively identified subgroups among stroke survivors, supporting tailored interventions in occupational therapy to improve rehabilitation outcomes. Further research is recommended to validate these findings in diverse populations. Plain-Language Summary: This study explored quality of life among stroke survivors. Three groups were identified: those with high, moderate, and low quality of life. Factors such as age, social relationships, and education level influenced quality of life after stroke. These findings can help occupational therapists create personalized care plans to support survivors in recovery, focusing on social connections, autonomy, and daily activities.