This paper presents a study of short-term load forecasting using Artificial Neural Networks (ANNs) and applied it to the Nigeria Electric power system. This gives load forecasts one hour in advance. The inputs used for the neural network are the previous hour load, previous day load, and hour of the day. The neural network used has 3 layers: an input, a hidden, and an output layer. The input layer has 3 neurons, the number of hidden layer neurons can be varied for the different performance of the network, while the output layer has a single neuron. An absolute mean error of 2.84% was achieved when the trained network was tested on one week’s data. This represents, on average, a high degree of accuracy in the load forecast.