<p>The evaluation of circular economy (CE) in iron and steel industry serves to offer recommendations for the sustainable development of this sector. However, the existing evaluation exhibit limitations, including the neglect of information reliability and the subjectivity inherent in modernization processes. Therefore, this paper proposes a comprehensive Z-Entropy-Text Mining-MARCOS method (ZETMM) for evaluating CE in the iron and steel industry. Firstly, to resolve the issue of overlooked information reliability in previous studies, Z-numbers are employed to characterize CE-related data, and an improved comprehensive weighted distance measure for Z-numbers is proposed. Secondly, the innovative framework integrates a novel Z-number weighting method and Text Mining techniques to combine quantitative and qualitative data, thereby reflecting CE priorities as perceived by media outlets and governmental authorities. Additionally, the Z-MARCOS method is further proposed to effectively address the prevalent uncertainty in CE data. Demonstrated in a case study involving seven Chinese provinces, the proposed method demonstrates its practicality and robustness in real-world applications. The results show that Zhejiang, Shanghai and Guangdong achieved strong performance in the iron and steel industry’s CE development in 2019. Based on the results, targeted recommendations are put forward to promote CE advancement. This paper proposes an improved Z-number comprehensive weighted distance measure, a novel index weight calculation method and a new evaluation method under the environment of information with limited reliability. These contributions aim to provide scientific and reliable results for CE evaluation in the iron and steel industry.</p>