Propensity score methods are wildly used techniques for the evaluation of causal effects in observational studies. Although Rosenbaum and Rubin's (1983) original article focused solely on binary treatments, further studies generalize the methods to multi-valued treatments, continuous treatments, and multidimensional continuous treatments. Despite its potential, Stata offers plenty of packages for all the cases but the last one. This paper aims to introduce a new Stata package – GPSMD – that implements the propensity score generalization to multidimensional continuous treatment developed by Egger and von Ehrlich (2013). The article illustrates the econometric framework and presents the commands implemented. We finally go through a simple working example to show the commands and the capability of the method to overcome bias. Keywords: continuous multiple treatments, GPSMD, dose-response, generalized propensity score