To explore the causal path of various water traffic accidents in China Coast, a causal path analysis method for water traffic accidents based on Human factors analysis and classification system (HFACS) model, Bayesian network (BN) model and path model was proposed. Firstly, based on the HFACS model, 5 levels including 38 causal factors for water traffic accidents were identified from the investigation report of water traffic accidents in China Coast. Secondly, the K2 algorithm was used for BN structure learning, and combined with chi-square test results and prior knowledge to determine the BN structure. Next, the maximum expectation algorithm was utilized for BN parameter learning. Then, the sensitivity analysis method was used to extract the causal path of various water traffic accidents. Finally, the path model was applied to calculate the causal path coefficients of various water traffic accidents and test their statistical significance. The results indicate that there are respectively 7, 6, 3, 7, 4, 4, and 2 significant causative pathways for accidents such as collision, sinking, contact, grounding, fire/explosion, wind strike, and stranding, in China Coast. From the perspective of effect level of causal path, the largest causal path of both contact accidents and stranding accidents is “improper allocation of chart data → improper navigation plan → contact/stranding accident”.