<p>The stock exchange plays a vital role in driving global economic development. The growth and performance of publicly listed companies contribute significantly to the overall health of a nation’s economy, impacting the wider economic and societal environment. To stay competitive in an ever-evolving market, companies need to constantly evaluate their performance, compare it with that of competitors, and pinpoint areas for improvement. Given the proven ability of data envelopment analysis (DEA) to assess organizational effectiveness, this research aims to create an advanced DEA-based model for evaluating the performance of twenty chemical firms listed on the Tehran Stock Exchange. Recognizing the uncertainty inherent in real-world financial data, which often follows probabilistic patterns, a novel stochastic entropy method is introduced to determine the most influential performance factors. The findings highlight “Return on Assets” as the most significant among the fifteen evaluated criteria. To address uncertainty more comprehensively, a new fuzzy-stochastic DEA model, grounded in the Enhanced Russell Model, is proposed. Application of the model under various significance levels reveals that “Iran Petro” consistently outperforms its peers, while “Pardis Petro” demonstrates the lowest relative performance. The results remain robust across different α-levels, confirming the model’s stability and practical applicability in uncertain financial environments.</p>