Quality control and quality assurance of rubber compounds require intensive and basic investigation of the present process interrelations, caused by the complexity of the rubber compounding process. It has been proved, that both regression analysis and artificial neural networks are capable tools for the description of these interrelations. In this paper the possibilities and limitations of artificial neural networks predicting the resulting rubber compound properties compared to regression models are discussed.