The main objective of the voltage control in Electrical Power System (EPS) is to guarantee the quality of the energy supplied to consumers. The voltage must respect government regulated levels. Currently, on the Brazilian EPS, the voltage control task is carried out by system operators based on diverse information, such as current values, and trends of electric variables (voltages, reactive and active powers, their sensitivities in the control devices performance, amongst others). To fully train a operator in this task it is necessary one or two years, period that could be greatly reduced if a decision support system was available during the operator`s training. However, due to the great number of variables that must be analyzed and their nonlinearity, an automatic decision support tool, capable to treat nonlinear relations, is necessary. Therefore, this work proposes a system based on Artificial Neural Networks (ANN), with the objective to identify the necessity or not to use the voltage control resources in the EPS. The developed system is composed of three modules: Pre-processing; Event Analysis and Classification; and Post-processing. Such decision support system suggests the most adequate equipment maneuver in the voltage control task. In the case study, the proposed system was evaluated using the available voltage control equipments (reactors, capacitors and transformer taps) in the 765 kV Transmission System, main responsible trunk for the interconnection of South and Southeastern Brazilian systems. Using real time data, different ANN configurations have been tested. The best results were obtained with a structure composed of two neural networks, for each controlled equipment, presenting, in average, 80% accuracy in relation to maneuvers occurred in real time. Due to the problem complexity, the results were considered more than satisfactory, indicating the applicability of this technique for the development of the desired system.