Methodological basis for the synthesis of system models under conditions of uncertainty of project tasks

This article explores the methodological foundations of synthesizing system models under conditions of project task uncertainty in the Russian Federation. It explores the importance of a systems approach as a tool for scientifically describing complex managerial, technical, digital, and organizational-economic processes developing under conditions of incomplete data and a volatile external environment. Particular attention is paid to the classification of uncertainty factors, including information, resource, technological, institutional, and behavioral risks. The article substantiates the need to apply scenario analysis, risk modeling, multi-criteria assessment, and feedback mechanisms to improve the quality of project decisions. It demonstrates that synthesizing system models enables the alignment of project goals, resources, constraints, and expected results. A conclusion is drawn regarding the practical significance of adaptive modeling for developing project management in modern Russian conditions, increasing the sustainability of decisions, and reducing the likelihood of errors in the implementation of complex projects in various sectors of the economy, management, and technological development of the country.