Mixture models are helpful for complex data. A new method using Jeffreys’ priors for these models was tested. The prior for a Gaussian mixture model was found to be improper, but conditional Jeffreys’ priors for each parameter group were proper. Using these priors, the researchers approximated the posterior distribution and found it to be proper through simulation.