Purpose: This study explored the potential correlates of exercise self-efficacy among older adults with a self-reported diagnosis of arthritis. Methods: This study was a secondary data analysis and used a cross-sectional design. Data was collected from a convenience sample of Non-Hispanic White and Non-Hispanic Black individuals between 2006-2008 (N=208). Descriptive statistics were run to assess means and frequencies within the sample. Bivariate statistics (Pearson and Spearman correlations, T-tests and one-way analysis of variance) were run to examine relationships between the independent and dependent variables. Multiple linear regression analyses were conducted to examine independent predictors of self-efficacy for exercise (SEE) and barriers self-efficacy for exercise (BSE). Results: Participants were predominantly female (85.6%), white (62.9%), retired (58.1%) and had a mean age of 66.6 [10.7] years. For education level, 23.4% reported a Master’s degree or higher and 18.6% reported they had at most a high school degree or GED. Nearly 47% of the sample were classified as obese based on self-reported body mass index (BMI) and 68.3% of the sample were not meeting the American College of Sports Medicine physical activity (PA) recommendations. Participants reported a relatively high BSE (22.6) and an average SEE (22.7). Significant positive associations were seen with outcome expectation for exercise (EOE), social support, and total minutes of PA and negative associations with BMI, physical function, pain, and negative affect with SEE and BSE. Meeting the PA guidelines (t134.5=4.60, 95%CI= 4.7(6.71-2.68), p<0.001) and being white (t164=2.82, 95%CI=2.82(0.57-5.08), p=0.014) were associated with SEE and BSE (t165=3.42, 95%CI= 4.37(6.89-1.85), p=0.001) and (t164=2.34, 95%CI= 2.95(0.46-5.43), p=0.021), respectively. In regression analyses, significant predictors of SEE were education (p=.006), physical function (p=.006) and EOE (p<.001). Significant predictors of BSE were physical function (p=.020), social support (p=.031), EOE (p=<.001), education level (p=.037), and total minutes of PA (p=.022). The variables in the SEE model accounted for 50.5% (R=.737, R2=.505) of the total variance and the variables in BSE model accounted for 41.1% (R=.672, R2=.411) of the total variance of the model. Discussion: EOE appears to be an important predictor of SEE and BSE. Examining the temporal relationship between EOE and SEE is warranted.