Fishery stock assessment is a basic component of modern management, required to maintain sustainable fishery development. Traditional methods require a large amount of statistical data assessing yield, abundance index, and age structure. Due to limited funding and data for such surveys, only 1% of fish stocks have systematic assessments conducted. Therefore, it is difficult to assess maximum sustainable yield (MSY) or determine allowable catch for most fishery resources using traditional methods. In recent years, stock assessment using limited available data has become a focus of increasing academic research. A good assessment model based on incomplete data would allow managers to assess the risk of overexploitation, current population biomass, sustainable yield, optimal fishing mortality, and population status relative to reference points such as current total catch limits. These parameters can then be used to determine appropriate fishing limits for the target population. Such models use different assumptions and have different limitations. Therefore, it is necessary to select an appropriate model that will minimize error in the results when evaluating target resources. Where more than one model is available, they can be compared to assess which obtains the best results. In assessment of fishery resources using data-poor methods, more and more attention is being paid to characteristic life history parameters such as intrinsic growth rate, natural mortality coefficient, and so on. Under conditions that combine the yield of the evaluated population with the corresponding life cycle parameters, a more reliable MSY value or sustainable yield can be obtained. In this paper, assessment models based on life-history characteristics are divided into three categories:(1) models that only use life history parameters; (2) models that incorporate catch data and life-history parameters; (3) models that incorporate catch data, life-history parameters, and lifespan or age data. The introductions, data requirements, output results, and limitations of each model is reviewed and systematically analyzed. In addition, several common life-history parameter estimation methods are provided. A simple preliminary assessment of sustainable catch was conducted for North Atlantic blue shark () using Catch-MSY and DCAC models, and results were compared. Results calculated using the DCAC model are similar to those obtained with the Catch-MSY model. Maximum sustainable yield of blue shark was about 3.0×10⁴ tons. This paper also provides suggestions on use of data-limited models and applications to assessment of offshore fishery resources in China. The current survey of Chinese offshore fishery resources started late, and recorded data are relatively few, therefore most fisheries had difficulty estimating by traditional methods. The natural mortality coefficient of fish off China's coasts is generally >0.2; thus, assessment errors using DCAC and DB-SRA models will be large. The catch-MSY model can fit the present resource situation well, and is often used to evaluate fishery resources off China's coasts. In view of the low reliability of the upper limit estimate used by the Catch-MSY model to estimate environmental capacity, the SS model can be compared with it in future resource assessments to provide more theoretical support for protection and scientific assessment of offshore fishery resources.