The difference between two binomial proportions is commonly used in applied research. Since many studies encounter incomplete data, proper methods to analyze such data are needed. Here, we present a proper multiple imputation procedure for constructing confidence interval for difference between binomial proportions using Newcombe’s method, which is known to have a better coverage probability when compared with Wald’s method. We use both a conventional multiple imputation procedure for ignorable missingness and a two-stage multiple imputation for non-ignorable missingness. Using simulation studies, we compare our method to three other methods and provide recommendation for the use of such methods in practice. In addition, we show the application of our new method on a COVID-19 dataset.