Testability demonstration plays an important role in assuring the testability capability, which can decrease the fault diagnosis time and accelerate the maintenance actions. However, testability demonstration test with classical planning method has the problems of large fault sample size, high test cost, and long test period. A new testability demonstration planning method is proposed, which takes the component level data from both virtual and physical demonstration tests as prior information. Owing to the limitations of the testability modeling technology and relevant programming tools, the virtual testability prototype of the system level cannot be established and the virtual testability test data is not totally credible. So a data conversion method based on the information entropy theory is proposed to convert the component level virtual and physical test data into equivalent system test data, in which the data credibility is taken into consideration. The equivalent system test data is then used to get the prior probability density function of the testability indexes with an empirical Bayesian method. Then, a testability demonstration planning method of Bayesian posterior risk criteria is presented. Finally, the fault detection rate demonstration tests of a flight control system and a heating controller are taken as examples to verify the proposed method. The results show that the introduction of prior test data can effectively decrease the sample size and the credibility of the virtual testability test data can affect the test plan.