Accurate and real-time access to road adhesion information is the premise of the operation of the vehicle active safety control system． The roughness and wet condition of road have great influence on lateral stiffness． Based on this，road adhesion condition can be identified by estimating the lateral stiffness of tire under the steady- state cornering． First，the lateral force and slip angles of front and rear axle were obtained from the two-degree-of- freedom vehicle model． Considering the load transfer，the vertical tire vertical force was obtained． With the diffe- rence between the front and back axes，the sideslip angle which is more difficult to get was eliminated． Finally，the normalized tire lateral stiffness was estimated by the recursive least square method，and the estimated results under different road adhesion conditions were compared． Different from previous lateral stiffness estimation methods，the proposed method does not need to measure or estimate the sideslip angle，so it does not need expensive extra sen- sors． Moreover，the influence of load transfer on the estimation of cornering stiffness was taken into account． The proposed algorithm was verified through simulation and electric model vehicle road test． The simulation and experi- mental results show that the proposed identification algorithm can identify the road adhesion conditions when consi- dering load transfer．