Summary: The fault sample size which is required in existing testability demonstration test schemes may be reduced by using data in the development phase. However, the growth test data are “small samples” with “varying population”. A new testability verification method based on the Bayes theory is proposed. Firstly, the proposed method establishes a dynamic growth model of the test parameters based on multiple phases’ samples, which is used to describe the changing rule of equipment’s testability and predict the fault detection rate (FDR) and the fault isolation rate (FIR). Then, the prior distribution of the system’s FDR/FIR is calculated based on the maximum entropy principle. Finally, a new testability determination scheme is defined to verify FDR/FIR, according to Bayes maximum posterior risk rules with a small size of field trial data. The practical comparison shows that this method, in which the growth test data and field trial data can be fused effectively, can reach an evaluation conclusion with a high confidence level under small sample circumstance, and reduce the risk of evaluation.