Post-stratification is used in survey statistics as a method to improve variance estimates. In traditional post-stratification methods, the variable on which the data is being stratified must be known at the population level. In many cases this is not possible, but it is possible to use a model to predict values using covariates, and then stratify on these predicted values. This method is called endogenous post-stratification estimation (EPSE). In this paper, we investigate methods to automatically select the number of post-strata for EPSE. We do this in the context of models fitted by Random Forests with the stratum boundaries set at quantiles of the predicted distribution.