In this paper, the prediction model based on Bayesian is constructed for presenting cause and effect relationships between software structure features and software flexibility by consulting the experiential data and expert knowledge. In addition, the Bayesian networks learning technique is extended to find out the weak causal relationships in the software flexibility prediction model constructing. Finally the method and examples using the prediction model to assess software flexibility in the software architecture level are presented.