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Malaria is a major health problem in Senegal. Given the seasonality of the disease, the development of decision-support tools such as models to predict the occurrence of malaria epidemics would be of paramount importance in the fight against the disease. Thus, the present study contributes to a better understanding of the relationship between climate and malaria in order to improve the surveillance and management of this disease. The study was carried out in the Ziguinchor region using data covering an eight (08) year period, from 2015 to 2022. Two types of monthly data were used, namely meteorological data and health data (number of confirmed cases of malaria). The methodology adopted consisted of graphical analysis, simple linear regression and multiple linear regression. The most relevant parameters were selected using the "backward elimination" method. Finally, the model was validated using four (04) statistical tests (Shapiro-Wilk test, variance inflation factor test, Durbin-Watson test and Goldef-Quandt test), followed by a robustness check using the Taylor diagram.