In order to meet the demand of testability analysis and evaluation for complex equipment under a small sample test in the equipment life cycle, the hierarchical hybrid testability modeling and evaluation method(HHTME), which combines the testability structure model(TSM) with the testability Bayesian networks model(TBNM), is presented. Firstly, the testability network topology of complex equipment is built by using the hierarchical hybrid testability modeling method. Secondly, the prior conditional probability distribution between network nodes is determined through expert experience. Then the Bayesian method is used to update the conditional probability distribution, according to history test information, virtual simulation information and similar product information. Finally, the learned hierarchical hybrid testability model(HHTM) is used to estimate the testability of equipment. Compared with the results of other modeling methods, the relative deviation of the HHTM is only 0.52%, and the evaluation result is the most accurate. In order to meet the demand of testability analysis and evaluation for complex equipment under a small sample test in the equipment life cycle, the hierarchical hybrid testability modeling and evaluation method (HHTME), which combines the testability structure model (TSM) with the testability Bayesian Firstly, the testability network topology of complex equipment is built by using the hierarchical hybrid testability modeling method. Secondly, the prior conditional probability distribution between network nodes is determined through expert experience. Then the Bayesian method is Finally, the learned hierarchical hybrid testability model (HHTM) is used to estimate the testability of equipment. Compared with the results of other modeling methods , the relative deviation of the HHTM is only 0.52%, and the evaluation result is the most accurate.