Waste Stabilization Ponds (WSPs) are a widely utilized wastewater treatment technology, known for efficiently removing organic pollutants and pathogenic microorganisms. Their performance is influenced by environmental factors such as solar radiation, air temperature, and wind speed. Despite its role as a primary mixing mechanism in WSPs, wind speed has been largely underexplored in predictive modeling studies. This study analyzed 30 pairs of samples collected over 5 months (April to September, 2023) from the inlet and outlet of a facultative pond at the University of Nigeria, Nsukka, to evaluate Biochemical Oxygen Demand (BOD) removal efficiency and Faecal Coliform (FC) log reduction value (LRV). Regression models were developed using various combinations of radiation intensity, air temperature, and wind speed as predictor variables. Results revealed that average air temperature alone provided the most robust models, explaining over 88% and 95% of the variability in BOD removal efficiency and FC LRV, respectively. Radiation intensity showed limited predictive significance, while wind speed was not significant in any model. These findings highlight the dominant role of temperature in WSP performance and support temperature-centric models for optimizing wastewater treatment across diverse climatic settings.