<p>Pharmacophore modelling is widely used in drug discovery to highlight the key chemical features required for biological activity and to screen large libraries for promising hits. The usefulness of any pharmacophore model, however, depends on how well it is validated. This review brings together the main strategies for assessing pharmacophore model quality, ranging from classical metrics such as ROC-AUC, enrichment factors, and BEDROC to decoy-based evaluations such as DUD-E, as well as visual tools including cumulative gain and lift charts. We also discuss validation workflows built into platforms such as Schrödinger’s Phase module. Each method is described in terms of what it measures, early enrichment, discrimination between actives and decoys, or overall model robustness, and where it is most helpful. By outlining the strengths and limitations of these approaches, this review provides practical guidance for selecting appropriate validation methods and improving the reliability and predictive value of pharmacophore models in virtual screening.</p>