The fuzzy neural network is applied to the short-term load forecasting. The fuzzy rules and fuzzy membership functions of the network are obtained through fuzzy neural network learming. Three inference algorithms, i.e. the multiplicative inference, the maximum inference and the minimum inference, are used for comparison. The learning algorithms corresponding to the inference methods are derived from back-propagation algorithm. To validate the fuzzy neural network model, the network is used to Predict short-term load by compaing the network output against the real load data from a local power system supplying electricity to a large steel manufacturer. The experimental results are satisfactory.