Abstract: Assessing the current stock status of the Larimichthys polyactis, a fish species of high ecological and economic value, in the Zhoushan Fishing Ground is crucial for ensuring the sustainable utilization of its resources. In response to the decline in L. polyactis resources and the long-term lack of systematic statistical data in the Zhoushan Fishing Ground, this study employs stock assessment methods that require only short-term length-frequency data to clarify the current stock status and exploitation level of this population, thereby providing a scientific basis for its management and conservation. Based on length data from 772 individuals collected during four surveys from 2019 to 2024, growth parameters (the asymptotic length, L_inf, and the growth coefficient, K) were estimated using ELEFAN methods, while the natural mortality coefficient (M) was estimated using six empirical formulas. Different parameter combination scenarios were set up, applying both the Length-Based Spawning Potential Ratio (LB-SPR) and the Length-Based Bayesian Biomass (LBB) assessment methods. Sensitivity analyses were performed on input parameters, and results from both methods were integrated to evaluate stock status. The LB-SPR assessment indicated that the average relative fishing mortality (F/M) was 6.70, while the average spawning potential ratio (SPR) was only 0.05. The LBB assessment revealed that the average F/M was 9.97, the average relative biomass (B/B_MSY) was 0.09, and the ratio of mean length at first capture to optimal length at first capture (L_c/L_{c_opt}) was 0.70. Sensitivity analyses demonstrated that while quantitative results varied with input parameters, the conclusion regarding the stock status remained robust. All indicators consistently showed that the L. polyactis stock in the Zhoushan fishing ground is subject to extremely high fishing pressure, with critically low spawning potential and biomass, alongside significant population miniaturization. The conclusion is that L. polyactis resource in the Zhoushan fishing ground has suffered severe overexploitation. And the stock assessment methods and procedure used in this study demonstrates strong applicability and robustness under data-limited conditions, providing a methodological reference for stock assessment research in similarly data-limited fisheries.