Chemical Looping Combustion (CLC) represents a promising carbon capture technology pivotal in addressing the global challenge of reducing greenhouse gas emissions from industrial processes. This research employs fuzzy logic as a sophisticated framework to model and simulate the complex dynamics of CLC processes, including varied operational conditions, diverse fuel types, and environmental impacts. Through an innovative application of fuzzy logic systems, our approach significantly improves the precision of emission predictions, thereby facilitating the optimization of combustion efficiency and environmental compliance. The versatility and adaptability of fuzzy logic modeling offer a systematic method for evaluating and enhancing CLC technologies, demonstrating its value as a tool for scientists and engineers. This study contributes to the theoretical understanding of CLC process dynamics and provides a practical guide for designing and operating more efficient and environmentally friendly combustion systems. Several examples, including various oxygen carriers and fuels and CLC facilities, are also presented in the paper, confirming the comprehensive and versatile nature of the proposed approach. The findings underscore the potential of fuzzy logic to serve as a comprehensive framework for advancing CLC technologies, with implications for future research, design optimization, and policy formulation.