High-throughput, low-cost, and accurate predictions of thermal properties of new materials would be beneficial in fields ranging from thermal barrier coatings and thermoelectrics to integrated circuits. To date, computational efforts for predicting lattice thermal conductivity (κL) have been hampered by the complexity associated with computing multiple phonon interactions. In this work, we develop and validate a semiempirical model for κL by fitting density functional theory calculations to experimental data. Experimental values for κL come from new measurements on SrIn2O4, Ba2SnO4, Cu2ZnSiTe4, MoTe2, Ba3In2O6, Cu3TaTe4, SnO, and InI as well as 55 compounds from across the published literature. To capture the anharmonicity in phonon interactions, we incorporate a structural parameter that allows the model to predict κL within a factor of 1.5 of the experimental value across 4 orders of magnitude in κL values and over a diverse chemical and structural phase space, with accuracy similar to or better than that of computationally more expensive models. © 2017 American Chemical Society.