Nursing homes have shifted from task-focused to person-centered care (PCC) environments. Understanding resident preferences for daily care and activities is fundamental to PCC. Examining resident similarities based on preferences may be useful for group or community-wide PCC planning. The aims of the current study were to group residents according to similarities in preferences and determine the factors that predict membership in these groups. A latent class analysis of resident preferences using data from the Minimum Data Set (N = 244,718) was conducted. Resident function, depression, cognitive impairment, and sociodemographics were used as predictors of class membership. The four-class model showed residents cluster around overall interest or disinterest in having choices about daily care and activities or specific interest in either care or activity preferences. Race and ethnicity, cognitive impairment, and depression predicted class membership. Findings suggest that residents can be grouped by preferences and knowledge of resident group membership could help direct efforts to systematically meet resident preferences. [Journal of Gerontological Nursing, 45(8), 7-13.]. Copyright 2019, SLACK Incorporated.