The aim of the present research is to design a performance management model based on think tank network participation. In terms of objective, this research is exploratory, and in terms of implementation, it is qualitative. The statistical population consists of 19 university professors, managers, and public administration experts, who were selected using purposive sampling. The research instrument is a semi-structured interview. For data analysis, the coding method and MAXQDA software were used. The findings revealed that 543 initial codes were extracted, which were classified into 122 indicators, 32 components, and ultimately 13 dimensions. The model of ‘Government Performance Management Based on Think Tank Network Participation’ encompasses five key dimensions: first, ‘identifying and formulating the organization’s issue system’; second, ‘designing and validating the organization’s performance indicators’; third, ‘monitoring and measuring the organization’s performance’; fourth, ‘analyzing performance and providing feedback to the organization’; and fifth, ‘improving organizational performance and organizational learning’. Overall, government performance management based on think tank network participation represents a systematic response to the inefficiencies of traditional and linear approaches to governmental performance evaluation. From problem identification to organizational learning, this approach delineates a ‘participatory-feedback’ cycle in which think tanks and elite networks are no longer mere external observers or critics, but rather strategic partners of the government in the path toward transparency, intelligent monitoring, and continuous improvement. While compensating for structural weaknesses in the existing evaluation system, this approach provides a platform for learning-based, accountable, and problem-oriented governance