At this paper a new methodology is introduced, based on neural networks (NN) & genetics algorithms (GA), which “put data to work” and provides the best possible solution for a given design based on the available data. The goal of this development is to provide designers with a tool that can be used to select the optimum design for a given product. This is possible thanks to the optimization of the NN itself trough GA implementation based on the available training data. Genetic algorithms have been used for neural networks in two main ways: to optimize the network architecture and to train the weights of a fixed architecture.