The use of predictive models can facilitate the inclusion of shear parameters in asphalt mixture evaluation and design processes. Unlike more extensively studied tension–compression models, the currently existing shear model, the Hirsch model, has unrealistic constants, particularly for the prediction of phase angle. Aiming at an improved predictive model in shear, this study employs a simple shear apparatus to experimentally analyse the linear viscoelastic properties of asphalt mixtures for road paving. Master curves were constructed and compared between different asphalt mixtures. Additionally, the test results were also analysed in the Black space and the Cole-Cole space. The dynamic shear response of asphalt mixtures was thereafter modelled on the basis of the Hirsch model. As the original model for phase angle prediction was found to be unrealistic, a particular focus in this study was put on identifying realistic empirical relationships for predicting the phase angle of asphalt mixtures in shear. More reliable shear test results of asphalt mixtures were used to calibrate the model, and extra test data were utilized to validate the calibrated model. It is indicated that the predictive model after calibration could deliver results of greatly improved accuracy, especially at the high-frequency and low-frequency ends. The analysis and modelling also leads to realistic empirical relationships for predicting the phase angle of asphalt mixtures in shear. The experimental verification confirms the good prediction accuracy of the calibrated model and proposed empirical relationships.