The purpose of the research is to improve the quality of assessment of functional states of working memory by developing a method for synthesizing fuzzy decision rules.Methods. To monitor the state of various RAM blocks, a set of techniques was selected: reaction time assessment; searching for a signal in noise; "identification"; full reproduction; identification of missing digits; Memory. To synthesize decision rules, additional methods were used to assess such properties of attention as switchability, concentration and stability, for the implementation of which a device for monitoring the properties of the attention and memory function was used. To select an adequate mathematical research apparatus, an exploratory analysis of the structure of the processed data was carried out, according to which it was established that the selected classes of RAM states are of a fuzzy nature with uncertain boundaries of their intersections. Taking this into account, the methodology for the synthesis of hybrid fuzzy decision rules was chosen as a mathematical research tool, which was modified by developing a new method for fuzzy assessment of the functional state of RAM based on the characteristics of its properties.Results. In the course of the research, models were synthesized to assess such characteristics of the functional state as levels of fatigue, psycho-emotional stress and the functional state of RAM using the full reproduction method. The resulting models can be used to synthesize decision rules for forecasting, early and differential diagnostics of the functional state, assessing the quality of work of the operator of human-machine systems and the health status of RAM.Conclusion. The paper proposes a method for synthesizing fuzzy decision rules for assessing the functional state of RAM based on the characteristics of its properties using techniques obtained from the results of microstructural analysis. Fuzzy decision rules were obtained for assessing the level of fatigue, psycho-emotional stress and the functional state of RAM using the full reproduction method. During expert assessment and mathematical modeling, it was shown that confidence in the correct assessment of the level of functional state exceeds 0,95.