Bone drilling process is one of the most common processes in the orthopedic surgeries and bone break treatments. It is also very frequent in dentistry and bone sampling operations. Bone is a complex material and the machining process itself is sensitive, so bone drilling is one of the most important, common and sensitive processes in Biomedical Engineering field. Orthopedic surgeries can be improved using robotic bone drilling systems and mechatronic bone drilling tools. In the present study, multiobjective optimization is performed on the temperature and trust force at two steps. At the first step, two regression models are developed for modeling the temperature and force in bone drilling process considering three design variables, namely tool’ s rotational speed (V), feed rate (f) and tool diameter (D). At the second step, using the regression models, multi-objective genetic algorithm is used for the Pareto based optimization of bone drilling process considering two conflicting objectives: temperature and force. It has been found out that there are considerable connections and feasible principles for an optimal design of the process in case of applying Pareto-based multi-objective optimization; otherwise, these interesting results would not be discernible.