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To reduce energy consumption and improve service stability and security, various design methods of cutterhead based on lightweight, modal optimization and life prediction were adopted. In the present work, a multi-disciplinary design optimization (MDO) methodology is presented and subsequently applied to the development of cutterhead. According to the requirements of the cutterhead process and the results of sensitivity analysis, the design parameters of each discipline were determined. To alleviate the computational cost caused by calling the results of finite element method (FEM) in design optimization, the Kriging model was employed to approximate the highly nonlinear implicit relationship between the mode frequency, fatigue life and the design parameters. Then, the system-level optimization model and the subsystem-level optimization model of mass, mode frequency and fatigue life were established based on collaborative optimization (CO). Finally, genetic algorithm (GA) was used for iterative optimization between the system-level and subsystem-level model to obtain the overall optimization results. The results showed that the mass of the cutterhead was finally reduced from 90.4 t to 88.5 t, the first-order modal frequency raised from 32 HZ to 37 HZ, and the fatigue life raised from 3.0E5 cycles to 5.5E5 cycles. [ABSTRACT FROM AUTHOR]