Nine static models (seven basic and two mechanistic) and their respective cutoff values used for predicting cytochrome P450 3A (CYP3A) inhibition, as recommended by the US Food and Drug Administration and the European Medicines Agency, were evaluated using data from 119 clinical studies with orally administered midazolam as a substrate. Positive predictive error (PPE) and negative predictive error (NPE) rates were used to assess model performance, based on a cutoff of 1.25-fold change in midazolam area under the curve (AUC) by inhibitor. For reversible inhibition, basic models using total or unbound systemic inhibitor concentration [I] had high NPE rates (46-47%), whereas those using intestinal luminal ([I]gut) values had no NPE but a higher PPE. All basic models for time-dependent inhibition had no NPE and reasonable PPE rates (15-18%). Mechanistic static models that incorporate all interaction mechanisms and organ specific [I] values (enterocyte and hepatic inlet) provided a higher predictive precision, a slightly increased NPE, and a reasonable PPE. Various cutoffs for predicting the likelihood of CYP3A inhibition were evaluated for mechanistic models, and a cutoff of 1.25-fold change in midazolam AUC appears appropriate.