A multilayer transformer condition assessment model is built by taking both fuzziness and randomness in uncertainty into consideration.The framework of assessment is divided into three layers of subsystem assessment，system assessment and overall assessment，respectively.In the first layer of subsystem assessment，the relationship between quantitative index relative deterioration degrees and grades is expressed in the normal cloud model.Then the matter-element cloud model provides the association degrees between the quantitative indices and grades.By referring to the optimal weights，the condition assessment results of all subsystems in the quantitative assessment system are obtained.Finally random processing and Bayesian approximation of the original evidence is performed.The integral assessment results are obtained by merging the assessment results of the subsystems and systems based on the D-S evidence theory.The feasibility of the model proposed is verified through field test data，providing transformer condition assessment with a new line of thought.