The article introduces a method called predictive recursion for estimating unknown priors in empirical Bayes problems. This method is fast and effective for estimating mixing distributions. The researchers show that predictive recursion-based procedures are asymptotically optimal in certain cases. They apply this method to predict baseball batting averages during the season, and find that it performs well in predicting errors and capturing underlying features.