The purpose of the research was to improve the control of air defence firepower using fuzzy networks of target installations, enhancing the efficiency and accuracy of defensive actions. The research niche of this article is the optimization of decision support systems in air defence through the application of fuzzy logic to improve real-time threat assessment and response accuracy. The study hypothesized that the integration of fuzzy networks into air defence fire control would lead to improved decision-making accuracy and reduced response time under conditions of uncertainty. The methodology involved data collection using radar, acoustic, and infrared sensors; modelling of fuzzy systems with specialized software; the development of fuzzy rules for threat assessment; and the simulation of real combat conditions to evaluate system effectiveness and its integration with existing detection and tracking equipment. The results demonstrated that the proposed decision support system significantly enhances threat assessment accuracy, reduces reaction time, and improves overall air defence effectiveness. Simulation tests confirmed a notable increase in the speed and precision of defensive measures, highlighting the adaptability of the system to dynamic combat conditions. Furthermore, the integration of fuzzy networks with existing detection and tracking technologies facilitated rapid data processing and optimized firepower management, leading to cost reductions. The study contributes to the advancement of decision support methodologies in air defence by introducing an innovative approach based on fuzzy logic, which enhances the accuracy and efficiency of decision-making under conditions of operational uncertainty. Future research should focus on validating the system's effectiveness in real-world deployments to further refine its performance.