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With the implementation of the new international conventions, higher evaluation requirements for a marine engine room simulator have been put forward. Based on the cloud theory, an improved fuzzy comprehensive evaluation method was studied: First, the Delphi method was adopted to get the original cloud drops of the judgments, and the original judgment weight clouds were generated by the backward cloud generator. Second, the judgment cloud matrix was built using the comparison results of the original judgment weight clouds, and the cloud weights of the evaluation factors were further calculated. Third, the appraisal grade clouds were generated, and the cloud appraisal vector taking into account the importance of each factor for each appraisal grade was calculated. Finally, the evaluation cloud result <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula> was aggregated, and the similarity vector between <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula> and the grade clouds was calculated. The calculation process reflects an effective uncertainty conversion between a qualitative concept and quantitative characteristics. The effectiveness was verified using three interrelated examples. The results show the following: the expectation of <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula> is mainly determined by the operating process and, second, by the expectation of the cloud weights; the uncertainty index and the randomness index of <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula> are determined by the parameter values of the cloud weights and the impact of the closest grade cloud; and the similarity vector is directly affected by <inline-formula> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula> and the distribution of the grade clouds. The introduction of cloud model theory into fuzzy comprehensive evaluation is an effective evaluation method.