Our aim to study the annual variation of ICSI cycle outcome is it related to calendar seasons or weather temperature in our geolocation as retrospective study We analyzed 3586 fresh first completed ICSI cycles from (2011- 2016) in our center. Cycles were assigned to one of 4 calendar-seasons then to one of 2 temperature centiles: (? or < 50th centile: 20°C) depending on date of ovum pick-up. Regression models (MR and BNLR) were set to compare predictive values of 6 variables: female-age, number of grade A embryo transfer (NET), blastocyst ratio (RBL), calendar-season, temperature-centile, day-light-duration-centile for implantation and clinical pregnancy rates as primary outcomes. No significant differences were found between cycle features or outcome of calendar seasons. While cycle features between temperature centiles were comparable, cycle outcome in cold and hot weathers respectively were implantation rate (IR) 12.7%, 14.5% {OR & 95% CI 0.85 (0.76-0.96), (P=0.0098)}, cumulative pregnancy rate (CPR) 39.8%, 43.8% OR & 95% CI 0.84 (0.73-0.96) (P= 0.009)}. Using multiple regression (MR) for IR & binomial logistic regression (BNLR) for CPR employing 6 variables significantly predicted both IR and CPR (p < .000) but, day- light duration, calendar-season did not significantly add to prediction (p>0.05). in this study Absolute RR = 4 and Relative RR = 9. %, NumberNeeded -to -Treat = 25. We concluded that Weather temperature not Calendar season independently predicts better implantation rate (IR) and cumulative pregnancy rate (CPR) in ICSI as shown by regression analysis.