Abstract: In medical statistics study, non-inferiority test for two independent binomial distribution parameters is a very important problem. The constrained maximum likelihood test statistic cannot control the type I error rates for some cases be investigated. In this article, we use the fiducial inference methodology in order to develop more powerful tests for Non-inferiority based on the ratio between two independent binomial distributions. We present a broad Monte Carlo comparison between different tests for non-inferiority, confirming the preference of the proposed method from a power perspective. Simulation studies suggest that our MF test can control the type I error rates and its empirical type I error rate are much closer to the prespecified nominal significance level than those of other tests well with competitive powers.