The article is devoted to the analysis of the transformation of the methodology for forecasting business processes at enterprises of the agro-industrial complex in the context of technological modernization. The paper clarifies the conceptual framework and examines the key technological trends that define new objects for forecasting. A systematic review of the evolution of methodological approaches is conducted, from statistical methods and expert assessments to predictive analytics based on machine learning and digital twins. The main challenges of modern methodology are identified, including the gap between technological and managerial levels, the lack of economic justification, and the difficulties in integrating heterogeneous data. A conceptual scheme of a multi-level forecasting system integrated into the enterprise's digital platform has been proposed. Based on the apparatus of aggregated production functions and scenario modeling, an approach to assessing the expected effectiveness of technological modernization has been substantiated. Promising directions for developing methodology have been formulated, including the development of hybrid models and standards for evaluating forecasting systems in the agro-industrial complex.
Niyaz N. Anvarov (Mon,) studied this question.