The aim of this investigation is to develop a model to predict some most important mechanical properties of Al-Si-Mg alloy and establish a correlation between different processing parameters and the mechanical properties of the investigated alloy. A most popular computational modelling tool which worksbased on a statistical approach known as artificial neural network (ANN) model is used in this investigation to predict various mechanical properties of the material. The model is based on multilayer feed-forward neural network. Alloy chemical compositions, modifier used, fabrication techniques and heat treatment parameters are chosen as the input for the network. The outputs of the network are some important mechanical properties namely tensile strength, yield strength, elongation and hardness of the material. A large dataset was created by collecting the input-output pairs from existing literature for efficient prediction of the model. Finally, the effect of all the processing parameters on the mechanical properties are predicted using the created network and the results are explained based on metallurgical point of view.