The objective of this paper was to present how a neural networks technique could be applied to predict the outcomes of a simultaneous production of the inulinase and invertase by Aspergillus niger and Kluyveromyces marxianus, as well as to optimize the conditions of he said production using a batch shaken culture. The inputs of the network represented the quantities of individual components of the medium (NH₄NO₃, (NH₄)₂HPO₄, KH₂PO₄, MgSO₄·7H₂O, yeast extract, inulin), the type of a microorganism, and the cultivation time, the temperature of enzymes biosynthesis, whereas the outputs represented: the activity of inulinase and the invertase. In experiments with Aspergillus niger and Kluyveromyces marxianus, the content of MgSO₄·7H₂O and inulin showed the highest effect on the final production result of the two enzymes. The NH₄NO₃ and the (NH₄)₂HPO₄ were the second important components of the medium. The content of FeSO₄·2H₂O and KH₂PO₄ had the lowest significant effect on the production of inulinase and invertase.