Previous research (Heit & Rotello, 2010; Rips, 2001; Rotello & Heit, 2009) has suggested that differences between inductive and deductive reasoning cannot be explained by probabilistic theories, and instead support two-process accounts of reasoning. We provide a probabilistic model that predicts the observed non-linearities and makes quantitative predictions about responses as a function of argument strength. Predictions were tested using a novel experimental paradigm that elicits the previously-reported response patterns with a minimal manipulation, changing only one word between conditions. We also found a good fit with quantitative model predictions, indicating that a probabilistic theory of reasoning can account in a clear and parsimonious way for qualitative and quantitative data previously argued to falsify them. We also relate our model to recent work in linguistics, arguing that careful attention to the semantics of language used to pose reasoning problems will sharpen the questions asked in the psychology of reasoning.