This study proposes an effective and powerful approach for analyzing the performance, credit rating, and ranking of mutual funds, taking into account their inherent network structures and the uncertainties prevalent in financial markets. To this end, the network structure and internal operations of mutual funds are modeled using a network data envelopment analysis (NDEA) approach based on collective efficiency decomposition. Additionally, to address uncertain and fuzzy data, a hybrid method combining possibilistic programming (employing possibility and necessity measures) and chance-constrained programming is utilized. Finally, the efficacy of the proposed fuzzy NDEA approach, developed under both optimistic and pessimistic scenarios, is validated using data from several active mutual funds in the Iranian capital market. The results highlight the capability of the proposed methodology in evaluating performance and analyzing the efficiency of mutual funds.