A reliable and continuous supply of electrical energy is necessary for the functioning of today’s complex society. Because of the increasing consumption and the extension of existing electrical transmission networks and these power systems are operated closer and closer to their limits accordingly the possibilities of overloading, equipment failures and blackout are also increasing, furthermore, we have an additional obstacle which is that electrical energy cannot be stored efficiently, so, electrical energy should be generated only when it's needed. Due to the fact that world is facing a lack of oil reserves and the difficulties related to have alternative sources to generate electrical power, then, electrical load forecasting is considered as a crucial factor in electrical power system either from economical or technical point of view on both planning and operating levels. This research introduces a short term electrical load forecasting system by using artificial neural networks with a simulation in Matlab environment in addition to an interface for the system and all that is depending on previous load data and weather parameters in Tartous province.