The invention relates to a data modeling based wearing monitoring and early-warning method for a variable pitch bearing of a wind turbine. The method includes the following steps: (1) data collection;(2) data pre-processing; (3) sample marking; (4) feature construction; (5) model construction; (6) algorithm verification; (7) model deployment. The method of the invention is high in effectiveness and accuracy, realizes a wearing monitoring and early-warning function for a variable pitch bearing of a wind turbine through modeling and predication by means of common sensor data, such as wind speed, power, rotational speed, pitch angle and pitch motor current, recorded by an SCADA system of the wind turbine, and has the characteristics of low cost, high efficiency, strong interpretation and thelike.