Combinatorial testing (CT) is a widely-used technique to detect system interaction failures. To improve the test effectiveness of CT, prioritized combinatorial testing inputs priority weights of parameter-values, and generates combinatorial test suites based on the weights. This paper proposes a method to automatically determine the weights of parameter-values by Bayesian inference using previous testing results. Using two open source projects, we evaluate the fault detection effectiveness of the proposed weighting based prioritized combinatorial testing.