Load forecasting is crucial in power system energy management, aiding planning and operations. This chapter focuses on using the Adaptive Neuro-Fuzzy Inference System (ANFIS) to model Hossana City’s power consumption in Ethiopia, forecasting beyond the available data for the next decade. To address the challenges of complex and widely distributed power systems, this study incorporated demographic factors. Performance evaluations show that ANFIS outperforms ANN, with a 2.0196% improvement in the mean absolute percentage error (MAPE) and 2.859984 in the root mean squared error (RMSE). The model demonstrates effective load forecasting based on previous data training and promises reliable future predictions.