The failure of the main engine's crankshaft in service on a large ocean-going cargo ship is a major operational and mechanical calamity. Despite the fact that crankshaft damage is rare, it is quite costly. Given the financial implications for shipowners and hull and machinery (H&M) insurance companies, it is crucial to identify the causal factors of the crankshaft damage to prevent reoccurrence. Hence, this paper models the causal mechanism of crankshaft failure. For this goal, this research investigates the probabilistic relationships among the crankshaft failure causal factors which are unveiled qualitatively and quantitatively employing the Fuzzy Bayes Network (FBN) approach. Axiom tests and sensitivity analysis afterward are performed to enhance the accuracy of outcomes. It is found that vessel personnel sourced fault has the highest effect on the explanation of crankshaft damage occurrence.