The present work introduces an expert system that automatically selects and designs rolling sequences for the production of square and round wires. The design strat- egy is aimed at reducing the overall number of passes assuming a series of process constraints, e.g., available roll cage power and torque, rolls groove filling behaviors, etc. The method is carried out into two steps: first a genetic algorithm is used to select the proper rolling sequence allowing to achieve a desired finished product; then, an optimization roll pass design tool is utilized for proper design of roll passes. Indeed, an artificial neural network (ANN) is utilized to predict the main geometrical character- istics of the rolled semi-finished product and technological requirements. The ANN was trained with a non-linear finite element (FE) model. The proposed methodology was ap- plied to some industrial cases to show the validity of the proposed approach in terms of reduction of number of passes and search robustness.