Maritime transportation safety has encountered unprecedented challenges arising from abrupt changes in various risk attributes in recent years, including natural weather and non-traditional security threats. This study presents a novel two-phase framework for assessing the maritime transportation risk. Firstly, a fuzzy Bayesian network considering multi-level node relationships was constructed to more accurately assess the transportation risk in various sea areas. In the second phase, RF-Shapley was developed to identify crucial risk nodes that exert substantial influence on transportation risk within individual sea areas. The results showed that transportation risk was the lowest in the South Asian and the highest in the Middle East waters. Critical risk nodes were different for each sea area, such as pirate attack node in Southeast Asian waters, extreme weather node in Northeast Asia, changing these nodes would be more helpful in improving transportation safety. Moreover, the contribution of critical risk nodes exhibited variations, such as combating terrorism and piracy were more conducive to reducing transportation risk in Middle Eastern waters, while ship accidents node be low contribution. These results offer valuable insights for evaluating transportation risk in uncertain environments and can serve as a reference for stakeholders to devise tailored policies and action plans.