Context. The article describes the results of research into the development of a new methodology for forecasting the individual resource of technical systems, which is a topical, but still not solved, problem, especially for small-series or single objects of control. This circumstance determines the relevance of the material presented in the article. Objective. The goal of the work is the development of a new methodology for forecasting the individual resource of technical systems, including unique and small-series ones. Method. A new methodology for forecasting the individual resource of technical systems is proposed, which is based on the identification of the trend model of the monitored parameter, performed on the basis of the results of regular monitoring of the technical condition of various industrial equipment, including small-series or manufactured in single copies. One of the coefficients of the model, which is determined in the identification process, is numerically equal to the predicted resource. Based on the known value of the resource and the measured value of the control parameter, the value of the linguistic variable is calculated, the results of comparison of which with the standard set of verbal quantities – “terms” – determine the degree of criticality of the technical condition of the equipment under control. Results. The methodology of forecasting an individual resource and evaluating the technical condition of industrial equipment, including unique and small-series equipment based on this degree of criticality, was implemented in the software product and used in assessing the degree of criticality of a hydro turbine – a typical representative of small-series products. Conclusions. The conducted experiments confirmed the expected effectiveness of the methodology for forecasting the individual resource and the efficiency of the software created on its basis, which makes it possible to recommend the methodology and software product for practical use in solving problems of forecasting the resource and diagnosing the technical condition of various industrial equipment. Prospects for further research consist in the hardware implementation based on stationary, mobile and embedded control systems developed methodology for forecasting the individual resource of mechanical systems.