This research explores the intricate relationship between weather-related variables and the transmission dynamics of two pivotal diseases: COVID-19 and dengue. Our primary goal is to advance our understanding of how climate factors influence the occurrence and spread of these diseases through a comparative analysis. In the context of the pressing need for accurate prediction systems, our research aims to contribute to the refinement of public health planning and decision-making strategies. In this work, our findings underscore the superiority of certain models in predicting epidemic outbreaks. Notably, Random Forest consistently demonstrated exceptional performance across all metrics for both COVID-19 and Dengue predictions. The model exhibited superior accuracy, precision, and correlation with actual values.