On the basis of a continuous process, the recommendation trust model is built for depicting indirect trust, the most complicated trust relationship. The model is also significant for the security and reliability of an open environment and open systems. After the factors influencing indirect trust are quantified, the filtrated recommendations are regarded as samples from the normal process, and the Bayesian estimation value of posteriori distribution expectation is obtained from calculation. Next, after an elaborate discussion of the trust evolution and the relationship between trust value and trustworthiness along with some propositions and proofs are proposed. Experimental data show that with the capacity of resisting malicious attacks improved, the model gives a more effective and precise result, which is also consistent with mathematical deduction.