Summary: We check the finite sample performance of maximum likelihood estimators of the parameters of a mixture distribution recently introduced for modelling ranks/preference data. The estimates are derived by the E-M algorithm and the performance is evaluated both from a univariate and bivariate points of view. While the results are generally acceptable as far as they concern the bias, Monte Carlo experiments show a different behaviour of the estimators’ efficiency for the two parameters of the mixture, mainly depending upon their location in an admissible parametric space. Some operative suggestions conclude the paper.