Rainfall variability in Lagos State, Nigeria, poses significant pluvial flood risks, particularly during the high-risk months from May to October. This study applies time series analysis using the ARIMA (2,0,1) model to forecast rainfall patterns from 1980 to 2022 and identify periods of heightened flood susceptibility. Stationarity was confirmed through the Augmented Dickey-Fuller test, and seasonal decomposition revealed consistent peaks during the rainy season. A critical rainfall threshold of 200 mm per month was used to define pluvial flood risks, demonstrating a recurrence interval of approximately one year for significant pluvial flood events. The model exhibited high predictive accuracy (RMSE = 103.11 mm), forecasting variable monthly rainfall patterns for 2023 that reflect continued seasonal fluctuations. Key findings attribute recurrent pluvial flooding to a combination of intense rainfall, inadequate drainage infrastructure, and rapid urbanization. The study recommends upgrading drainage systems, adopting real-time early warning systems, and integrating climate resilience into urban planning. Community engagement and collaborative governance are highlighted as critical for sustainable flood management. By providing actionable insights through predictive analytics, this research offers a robust framework for policymakers and urban planners to enhance climate resilience and mitigate socioeconomic impacts in Lagos State.