This study applies Box-Jenkins time series methodology to monthly confirmed malaria cases collected in Togo (2022-2024). ARIMA, SARIMA, and ARIMAX models were compared to evaluate temporal dynamics and forecasting performance. Results demonstrate strong annual seasonality, with SARIMA providing the most accurate and parsimonious model for predicting malaria incidence. The analysis highlights the relevance of routine surveillance data for epidemiological forecasting and public health planning in resource-constrained settings.