To address the fuzziness and randomness in safety evaluations of liquefied natural gas (LNG) chemical plants, a novel risk assessment method was proposed based on the normal cloud model. The proposed method was based on the selection of evaluation indicators from the perspective of intrinsic safety, which was used to evaluate the severity and likelihood of accidents through expert judgment. The weights of the indicators were determined by combining the analytic hierarchy process (AHP) and the criteria importance though intercrieria correlation (CRITIC). The risk matrix thresholds were softened using a forward cloud generator, and the evaluation results were optimized through a backward cloud generator to obtain cloud characteristic numbers and generate corresponding two-dimensional cloud maps. By comparing the actual cloud map with the standard cloud map, the risk levels of the evaluation indicators were determined. The results show that the model effectively integrates the expert opinions with aims of retaining the randomness and fuzziness, and providing the visualizes the risk assessment results. The novel method also provides a new risk assessment tool for the safety management of LNG chemical plants.