Objectives: The perceived temperature is an equivalent temperature based on the complete heat budget model of the human body. In this study, we aimed to analyze the effect of perceived temperature variability on the overall mortality among chronic kidney disease (CKD) patients. Methods: A total of 32,870 patients in Seoul participated in a retrospective cohort study (2001-2018) at three medical centers. Perceived temperature (PT) was calculated using climate factors, including air temperature from a nearby automated weather station, dew point temperature, wind velocity, anemometer height, and total cloud amount. Variability indices include standard deviation (SD), coefficient of variation (CV), average real variability (ARV), and successive variation (SV). The association of PT variability with mortality in CKD patients was assessed using the Cox proportional hazard model, adjusted for sex, age, body mass index, eGFR, hypertension, and diabetes mellitus. Results: During the 6.14±3.96 years, 3,863 deaths (13%) occurred. We confirmed the significant effects of monthly average PT variability (SD of monthly average PT: hazard ratio [HR] 1.05, 95% confidence interval [CI] 1.02-1.08) on mortality in multivariable analysis. Monthly minimum PT variability was associated with increased mortality (SD: HR 1.05, 95% CI 1.02-1.07; ARV: HR 1.08, 95% CI 1.04-1.12; SV: HR 1.06, 95% CI 1.04-1.10). Seasonal indices over 3 months showed that both average and minimal PT variability significantly increased mortality risk. However, maximal PT variability indices did not show an increase in mortality risk. Conclusions: Increased average and minimal PT variability is significantly associated with mortality risk among CKD patients.