By postulating that the random utilities associated with the choice options follow a multivariate normal distribution, Thurstonian models (Thurstone, 1927) provide a straightforward representation of paired comparison data. The use of Monte Carlo Expectation-Maximization (MCEM) algorithms and limited information approaches have been proposed to overcome the estimation intractability in analyzing data with a large number of choice items. However, these approaches have not yet been implemented into standard statistical software. For paired comparison data with a medium number of items, it is possible to use the free software program Mx to obtain parameter estimates. This article shows how Mx can be used to obtain parameter estimates for Thurstonian paired comparison models. A number of simulations are conducted to assess its validity in obtaining the estimates in comparison to MCEM. In addition, 2 datasets are analyzed to demonstrate the use of Mx in real applications.