The piecewise affine (PWA) model represents an attractive model structure for approximating nonlinear systems. In this paper, a procedure for obtaining the PWA model of the tire nonlinear cornering properties is introduced. In this approach, the highly nonlinear dynamic of the tire cornering properties is well approximated by a set of affine maps which relate inputs and outputs. These maps are defined in disjunctive regions in the regression space, itself composed of system inputs and outputs. The tire cornering properties tests are firstly carried out through a high-performance flat-plate test bench, thus the experimental data which can accurately reflect the tire cornering properties is obtained. On this basis, the PWA identification of the tire cornering properties is composed of the data clustering, the parameter estimation of the affine submodels and the calculation of the hyperplane coefficient matrices, which are respectively achieved by means of fuzzy c-means clustering, weighted least-squares and support vector machines. Finally, to verify the PWA model accuracy in approximating the tire nonlinear cornering properties, the comparison between the simulation results of the PWA identification model and the experimental data is conducted and the comparison results are analyzed.