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The wear state of a cutting tool is an important factor which affects machining quality. Therefore, monitoring tool wear is extremely essential to ensure workpiece quality and improve tool life. This paper models the milling forces of a worn tool and proposes a recognition method of milling tool wear state based on the influence relationships between the milling force features and tool wear. In the milling force model, the friction effect force and the shearing force are treated separately, and the friction stress distribution on tool flank is described. Then the force model is calibrated and verified through experiments. In the tool wear recognition method, the relationship between the milling force feature vector and tool wear is investigated. On this basis, the tool flank wear recognition method is proposed. A tool wear experiment is performed using superalloy material. In the experiment, the recognition results are expressed in confidence intervals which can represent the recognized tool wear more effectively and accurately. Finally, the scheme of tool flank wear online monitoring is proposed.