Background: Optimal quality of life is a universally desired outcome for nursing home residents, their families, and policy makers. To comprehensively evaluate the factors that influence quality of life among NH residents the biopsychosocial ecological (BPSE) model was used. Design: A secondary analysis using baseline data from the Restorative-Care Study was performed. Sample: The sample included 391 NH residents from 12 different NHs. Participants had a mean age of 83.7 years (SD=8.4) and the majority was female (80.3%), white (65.5%), and unmarried (83%). Measures: Measurement included socio-demographic variables (age, race, gender, marital status, length of stay), physical factors (pain, anemia, cognitive status), psychosocial factors (self-efficacy, outcome expectations) , and functional performance (activities of daily living, grip strength, gait and balance and falls). The dependent variable, quality of life, was measured using the Dementia Quality of Life Measure (total score and subscales: positive affect, negative affect, self- esteem, feeling of belonging, sense of aesthetics) and a single item individualized quality of life measure. Data analysis: Model testing was done using structural equation modeling and the Amos statistical program. Seven empirical based hypothesized models were tested (total quality of life score, each subscale, and the individualized single item measure). Results: None of the data fit the models, with each having 𝒳2 /df ratios greater than 3. However, education, gender, efficacy expectations, falls, cognitive status, pain and length of stay were all directly related to at least one of the subscales or total quality of life. The total variance in QOL explained by any of the hypothesized models was less than 10% indicating that additional factors not included in the hypothesized models are needed to optimally explain QOL of nursing home residents. Conclusion: The hypothesized models, developed based on the BPSE model and empirical research did not comprehensively explain the variance in QOL among NH residents. Further research is needed to test factors not included in this study (e.g., other comorbities, nutritional status, interpersonal relationships with staff, and social support) and thereby more comprehensively explain and intervene to optimize quality of life among these individuals.