Item difficulty should, in theory, be predictable from features derived from RPLDs, task characteristics, and linguistic complexity. This study evaluates the performance of multiple statistical and machine learning models in estimating item difficulty. We found similar results across all four models, the item features selected explain 53%–56% of the variance across all grades.