Abstract: Classical Box M-statisticis one of Likelihood Ratio Test (LRT) constructed under the multivariate normality distribution. The performance of classical Box M-statistic by using classical estimators suffers from masking and swamping effects when the outlier occurs in data set. To alleviate the problem, robust estimators are recommended. In this study, a robust Box M-statistic based on a S-estimator, Ms and M-estimator MM are proposed as the alternative to the classical Box M-statistic. Over the simulation study, the performance comparisonof classical, Ms and MM-statistics are measured using type 1 error rates. From the results, it showed that Ms (Box M-statistic based on S-estimator) has a competitive performance relative to MM and the classicalstatistic. In summary, Ms can be used for testing the equality of two difference covariance matrices or more when the data contains outlier.