Aluminizing processes are a well-known set of techniques industrially adopted to enrich in aluminum the surface layers of Ni-based alloys, thus improving their resistance to environmental interactions at high temperature. The results of aluminizing are described in terms of the presence, compositions and thickness of the sequence of the resulting surface diffusion layers. A combination of difficulties arising both from the mathematical and the material side restricted the number of available user-friendly models and their applicability to specific alloys or process conditions. The aim of the research work here presented is to overcome part of these difficulties. A synthesis of some well-established models was implemented in a robust numerical algorithm, that automatically prevents instabilities and convergence problems. Such numerical algorithm has been experimentally validated by comparing the results to the experimentally measured composition of profiles obtained for a set of vapor-phase aluminized samples of commercially pure Ni. The model was then applied to predict the effects of the process temperature and of the chemical composition of the surface.