This dataset contains predictions of habitat suitability of reed canarygrass (Phalaris arundinacea) in Upper Mississippi River floodplain forest understories from Pool 3 to Pool 13. Predictions were created using three machine learning algorithms (Bayesian additive regression trees, boosted trees, and random forest). This dataset contains rasters that provide habitat suitability predictions for each 12m raster cell that had forested landcover in 2010. In addition to one raster for each of the three algorithms an ensemble (mean prediction of all three algorithms) prediction raster for each pool is provided.