The use of fuzzy logic in modern forecasting tools allows performing operations to assess the state of technical objects. The innovation is that it creates conditions for immediate verification of experiments and hypotheses. The fuzzy logic model is designed to solve the problem of developing tool attributes in the field of quality engineering to improve the efficiency of the production process, as well as for the problem of predicting changes in the state of an object at future points in time. The efficiency of diagnostic programs is significantly increased when they are solved using the MATLAB Fuzzy Logic Toolbox package with the same content of control operations. The model includes five input parameters, such as recent data segment, cluster similarity, periodicity, neighbor similarity, historical error, and three output variables, such as forecast accuracy, clustering efficiency, and local approach suitability. At this time, the diagnostic algorithm is supplemented by an algorithm for solving the forecasting problem, which leads to the development of forecasting methods using various mathematical apparatus and taking into account the characteristics of the diagnostic object.