An existing low complexity, black box artificial neural network model (ANN model) is investigated towards its more general applicability in the field of high isobaric-isothermal inactivation of enzymes. The use of this non-linear modeling technique makes it possible to describe accurately synergistic effects of pressure and temperature in contrast with more classical models used in this novel area of food processing. The modeling approach will be illustrated on a new experimental data set, being used to validate the structural characteristics of the selected ANN model. Moreover, joint confidence regions, taking into account the correlation between model parameters, will be constructed. The results will be translated towards the raw experimental data. (C) 1998 IMACS/Elsevier Science B.V.