Depth profiling has been performed by using Auger electron spectrometry and X-ray photoelectron spectrometry in combination with Ar-ion sputtering. The data obtained by both surface-analytical methods have been evaluated by means of factor analysis and partly by applying artificial neural network in order to determine the compositional layering of different thin-films such as TiNx on Ti, Cr2O3/CrN sandwich layer, and copper oxide on Cu. Both multivariate statistical methods applied to the same data sets lead to results that agree well within statistical deviations provided that the structure of the artificial neural network is constructed appropriate to the actual problem.