A large working travel and a minimal stress are the most critical characteristics of a microgripper but they are conflicted each other. This paper develops a new efficient hybrid algorithm to solve the multi-objective optimization design for a sand bubbler crab-inspired compliant microgripper. The structure of sand bubbler crab-inspired compliant microgripper is inspired from the profile of sand bubbler crab. A surrogate-assisted multi-objective optimization is conducted by developing a hybrid approach of finite element analysis, response surface method, Kigring metamodel and multi-objective genetic algorithm. First, the data are collected by integrating the finite element analysis and response surface method. Subsequently, in the types of common surrogates, Kigring metamodel is adopted as an efficient tool to approximate the objective functions. And then, the Pareto-optimal fronts are found via the multi-objective genetic algorithm. The results indicated that the optimal results are at the displacement of 5999.9 µm and stress of 330.68 MPa. The results revealed that the optimized results are highly consistent with both the validation results. The accuracy of the surrogate models showed that the regression model is a good prediction. The proposed approach is useful tool to solve complex optimization designs.