This paper introduces identification results of human response to virtual 3D face stimuli. Observations of human reactions are done using preprocessed EEG (electroencephalogram) signals: excitement, meditation, frustration, engagement/boredom. Virtual 3D face features – distance between eyes, nose width, and chin width – are used as stimuli. Cross-correlation analysis demonstrated that dynamical relations between human reactions and stimuli exist. Input-output models describing relations between stimuli and corresponding human reactions are built. A new input-output model building method is proposed that allows building stable models with the least output prediction error. Models’ validation results demonstrate relatively high prediction accuracy of human reactions. DOI: http://dx.doi.org/10.5755/j01.itc.43.1.5927