The COVRATIO statistic has been used to identify the presence of outlier in data, which is based on deletion approach, where the determinant of covariance matrix for the full dataset excludes i-th row. This study proposes a novel discrimination method for the multivariate normal (MVN) distribution using the idea of COVRATIO statistic, denoted as COVRATIO(+i). The linear discrimination function (LDF) for MVN distribution will be compared to the COVRATIO(+i) statistic. Simulation results showed that the COVRATIO(+i) as discrimination method performs better than the LDF with lower misclassification probabilities in all cases considered. The interest in the discrimination method arose in connection with the study of an application to discriminate the shape of the human maxillary dental arches, thus COVRATIO(+i) statistic may be considered as an alternative.