As technology advances, so does the demand for electric power, steadily increasing over time. To ensure uninterrupted access to electricity round the clock, it’s imperative for generation facilities to synchronize with consumers’ evolving demands. Demand forecasting emerges as the key solution to avert any potential energy crises. In our latest endeavor, we’ve harnessed the power of artificial neural networks for precise electric demand forecasting. By leveraging data from an electric substation in Telangana, India, we’ve meticulously compared the performance of various neural network architectures. Through rigorous evaluation using metrics like MSE, RMSE, and MAPE, we’ve demonstrated the efficacy of our proposed support vector machine (SVM) approach. Our results unequivocally highlight that our SVM model stands out, delivering highly accurate forecasts for electric load demand.