This study presents a comparative analysis of two prominent time series forecasting models, Autoregressive Integrated Moving Average (ARIMA) and Artificial Neural Networks (ANN), in predicting monthly rainfall in Nigeria. Utilizing a quantitative methodology, the research analyzes average monthly rainfall data from January 1980 to April 2025, obtained from the Humanitarian Data Exchange. The dataset, known for its linear and nonlinear patterns, was preprocessed through linear interpolation and normalization to ensure compatibility with each modeling technique.