This package provides a data.frame processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner. vtreat prepares variables so that data has fewer exceptional cases, making it easier to safely use models in production. Common problems vtreat defends against: Inf, NA, too many categorical levels, rare categorical levels, and new categorical levels (levels seen during application, but not during training).