In order to effectively manage the ship capsizing risk caused by liquefaction of liquefiable solid bulk cargo during sea transport, based on ship kinematics and wave energy theory, AWQA hydrodynamic analysis software was used to simulate and analyze the external environmental loads encountered by ships while sailing in various typical sea areas. According to the theory of soil dynamics and results of triaxial tests, the equivalent analysis of the liquefaction risk of the cargo and the related assessment model were carried out. On account of the assessment model and numerical calculation samples, BP propagation neural network algorithm was applied to construct the predict model, which realized the quick intelligent assessment of the liquefaction risk of cargo shipping. The dominant expression of the BP quick predict model was obtained through the weight matrix and threshold matrix of the model, and the predict model was used to quick assess the liquefaction risk of four typical liquefiable solid bulk cargos under shipping environment. The predict results were in good agreement with the assessment results. This risk predict model can quickly and effectively assess the liquefaction risks of solid bulk cargo according to the parameters such as ship type and sea conditions, which provides an effective method for the front-line maritime supervision, and a good promotion for the development of IMSBC Code.