Electrical Energy is an essential commodity which significantly contributes to the economic development of any country. Many non-linear factors contribute to the final output of electrical energy demand. In order to efficiently predict electrical energy demand, many time-series analysis and multivariate techniques have been suggested. In order for these methods to accurately work, an enormous quantity of historical dataset is essential which sometimes are not available, inadequate and inaccurate. To overcome some of these challenges, this paper presents an Artificial Neural Network based method for Electrical Energy Demand Forecasting using a case study of Lagos state, Nigeria. The predicted values are compared with actual values to estimate the performance of the proposed technique.