The hybrid knowledge-based system proposed in this paper consists of a ＇＇stiff＇＇ segment, viz. the expert system based on the object-oriented approach, and a flexible part, viz. the neural network. Some of the input parameters of the problem and output parameters of the ＇＇stiff＇＇ system are presented as the fuzzy numbers. Detailed information is also presented about the development of the neural network. The most evident advantages of the proposed introduction of a hybrid architecture of the knowledge-based system are a faster evaluation and generation of design alternatives and support of systematic searches and storage of experience. In addition, the resulting ability to extrapolate results would be unattainable with separately acting stiff and flexible systems. A system for the estimation of the parameters of a mixing system for wastewater treatment is presented as an example to illustrate the principles of the hybrid system.