Extremely rapid flow-like landslides pose a significant hazard worldwide, however the analysis of the impact area and velocity of these flows is not routine. Semi-empirical equivalent fluid models are one of the most promising tools for performing this sort of analysis. These models are physically based, however certain parameters are determined through model calibration, using back-analysis of real landslide cases. The present analysis details a new methodology to calibrate equivalent fluid models. An equivalent fluid model, Dan3D, has been interfaced with the parameter estimation package PEST. PEST uses the Gauss—Marquardt—Levenberg algorithm to determine the set of model parameters that best minimize the misfit between model outputs and field data. A case history is provided to demonstrate how the new methodology is able to rapidly calibrate Dan3D, reduce subjectivity inherent in the calibration process and provide information onparameter uncertainty.