This work extends the methods of demographic inference based on the distribution of pairwise genetic differences between individuals (mismatch distribution) to the case of linked microsatellite data. Population genetics theory describes the distribution of mutations among a sample of genes under different demographic scenarios. However, the actual number of mutations can rarely be deduced from DNA polymorphisms. The inclusion of mutation models in theoretical predictions can improve the performance of statistical methods. We have developed a maximum-pseudolikelihood estimator for the parameters that characterize a demographic expansion for a series of linked loci evolving under a stepwise mutation model. Those loci would correspond to DNA polymorphisms of linked microsatellites (such as those found on the Y chromosome or the chloroplast genome). The proposed method was evaluated with simulated data sets and with a data set of chloroplast microsatellites that showed signal for demographic expansion in a previous study. The results show that inclusion of a mutational model in the analysis improves the estimates of the age of expansion in the case of older expansions.