Abstract
Various predictive calculations are actively used in modern scientific research, and economic and mathematical models are becoming particularly important. These methods and approaches are especially appreciated in the production environment, where they contribute to process optimization and informed decision-making. However, in the context of the development of industrial and economic activity, more and more enterprises are faced with the need to introduce mathematical models to improve the efficiency of innovation process management, which allows them to adapt to rapidly changing conditions and industry requirements. In this study, innovation processes are considered through the prism of the principles of sustainable development, which allows us to form the basis for interrelated concepts such as sustainable economy, cluster economy and industrial ecology. The practical significance of this research lies in its ability to offer a theoretical basis, empirical findings, and actionable recommendations for integrating sustainable development policies. These insights facilitate the transformation of innovation processes into a sustainable economic framework. The findings serve as a foundation for formulating strategies, policies, programs, roadmaps, and business models at multiple levels—macro, meso, and micro—within the agro-industrial sector.