The purpose of this secondary data analysis is to determine whether depression, cognition, functional status, health, and pain severity are predictors of day-to-day pain variability in older adults in long-term care settings. Seventy-seven adults aged 68 years and older were included in the multiple linear regression analyses. Pain severity mean and variability were measured over 30 days of daily self-reported pain levels. The Geriatric Depression Scale (GDS), Blessed Memory-Information-Concentration test, Physical Self-Maintenance Scale (PSMS), baseline pain severity, mean of daily health, and mean of daily pain severity were used as predictors. Pain variability was measured by examining intra-individual standard deviations of daily pain scores. Results show that global depression and pain severity are predictors of pain variability in that greater baseline depression and pain severity predicted higher pain variability. Daily mean pain and health were also found to be predictors of pain variability. Pain variability is an important characteristic that is not given enough emphasis in current literature. Understanding pain variability may give insight into older adults' experiences with both pain and depression, and may essentially improve quality of care and quality of life.