Abstract: Driven by environmental changes and fishing pressure, the stock status of Chelidonichthys spinosus has changed significantly in Haizhou Bay in recent years. However, due to the lack of data such as yields and fishing efforts, stock assessments are challenging for this species and the status of fishery exploitation remains unclear. In this study, we used length-frequency data obtained from the fishery surveys in Haizhou Bay from 2013 to 2023 to assess the stock status of C. spinosus using the Length-based Integrated Mixed Effects (LIME) model which is based on non-equilibrium assumptions. The uncertainty of the LIME model was further considered, and sensitivity analyses were conducted on parameters such as the steepness(h) in the stock-recruitment relationship, the natural mortality coefficient(M), and the length of the time series data. The results showed that the fishing mortality coefficients of C. spinosus were relatively high (F = 2.09 - 2.72) in Haizhou Bay from 2013 to 2023, significantly exceeding the biological reference point F₃₀ = 0.81. Recruitment of C. spinosus showed a fluctuating and declining trend, with the spawning potential ratio (SPR) ranged from 0.106 to 0.129, indicating that the stock was heavily overfished. The sensitivity analysis showed that the natural mortality coefficient (M) had a significant impact on the assessment results, while the impact of the steepness (h) was relatively small. The length of the time series had a significant effect on the estimation results of LIME, with a greater impact on the bias of F than on SPR. We highlight that LIME is capable to assess the stock status based on length-frequency data and is suitable for data-limited fisheries; however, it is sensitive to parameters such as natural mortality, and caution should be taken when the model is implemented in practice, regarding the estimation of critical parameters, the life history characteristics of target species, and the feasibility of survey data.