Abstract A proper hardening depth is critical to the load-bearing capacity of a part, and heat treatment, including carburizing quenching, can highly determine hardness distribution in part’s surface after manufacturing. This paper proposes ‘hardness prediction parameter optimization’ approach that deploys finite element method (FEM), artificial neural network (ANN), Genetic Algorithm (GA), des...