The primary usage of MDT is model fitting, otherwise known as Maximum Likelihood Estimation. This is the feature most users will be interested in.

Some users may additionally be interested in model sampling using Markov Chain Monte Carlo sampling, in MCMC sampling.

For adding your own models, or adapting existing models, MDT has a flexible component based plug-in system. This system, described in adding components allows you to extend MDT simply by placing python script files in your home directory.

MDT also offers a Maps visualizer to quickly visualize your MDT results. This visualizer is highly customizable and can provide paper ready figures.

Additional technicalities can be found in design concepts and Advanced configuration.