Abstract: TOPSIS and Bayesian network is introduced to the risk evaluation model for facilities of liquid chemical terminals. TOPSIS is used to screen the candidate risk indexes and 16 major indexes are identified to form the risk evaluation index system. The topography of the evaluation model is designed based on Bayesian network. The probabilistic inference concerning the nodes are fulfilled by Markov chain-Monte Carlo algorithm. The completed model is used, as an example, to evaluate the risks that a liquid chemical terminal at the Yangtze trunk line involves. The evaluation indicates that the risk level for the facilities is relatively low. The risk levels for facility subsystems are ranked as pipe system, storage facility, mechanical equipment and safety and protection equipment in descending order.