Abstract: Due to data limitation, most fisheries find it difficult to use traditional fisheries stock assessment methods to provide recommendations for fisheries management. As a result, data-limited assessment models have gainedincreasing attention, among which CMSY has become a widely used method internationally. However, studies indicate that CMSY is highly dependent on prior assumptions, and the specific impacts of different parameter priors on model outputs remain uncertain. To address this problem, we conducted a sensitivity analysis of CMSY by randomly selecting 200 fish and invertebrate stocks from different sea areas in the RAM Legacy Stock Assessment Database. The model estimation results, including biomass trajectory, MSY, B_MSY, F_MSY, B/B_MSY and F/F_MSY were systematically analyzed to examine their variations by incrementally adjusting the upper and lower bounds of the intrinsic growth rate (r), and the biomass levels at the start, middle and end years (B_start/K, B_int/K, B_end/K). The results indicate that: 1) Biomass trajectory, B_MSY, and F_MSY were significantly influenced by the lower bound of r, while B/B_MSY and F/F_MSY were more sensitive to the upper bound of B_end/K. MSY was less affected by the prior settings of the parameters. 2) Taxonomic classification at the order level exhibited no significant influence on the sensitivity of the CMSY method. 3) Variations in parameter priors were observed to induce quadrant transitions in the population stock status depicted in the Kobe plot, among which the upper bound of B_end/K showed the most significant effect. This study reveals that the CMSY method exhibited high sensitivity to parameter prior settings. It is suggested that careful parameter configuration and result interpretation are essential when utilizing this model.