In this paper, we focus our attention on sample size for destructive inspection and use ML-Ⅱ to estimate the upper limit of the Prior pdf for defective rate of populaton. After that, we consider inspection cost and losses of sampling error and we use Bayesian estimation method for expected total losses. Applying computerized numerical analysis method, we can find out the optimal sample size to minimize the total losses. Furthermore, we use the concept of sequential sampling, then we draw a sample, and inspect it in each sequential observation to determine whether to stop sampling and then making decision or not, to construct the decision chart of sequential sampling. In order to test and verify whether the Bayesian sequential sampling plan is superior to classical sequential sampling plan, we proposed a numerical example to carry on the comparison. Finally, we derived the concrete conclusions for future studies and practical applications.