In this study, the new predictive model for the micro-grinding process was developed by consolidating mechanical and thermal effects within the single grit interaction model at microscale material removal. The size effect of micro-machining was also included in the proposed model. In order to assess thermal effects, the heat partition ratio was experimentally calibrated and compared with the prediction of the Hahn model. Then, on the basis of this predictive model, a comparison between experimental data and analytical predictions was conducted in view of the overall micro-grinding forces in the x and y directions. Although there are deviations in the predicted micro-grinding forces at low depths of cut, these differences are reduced as the depth of cut increases. On the other hand, the optimization of micro machine tools was performed on the basis of the proposed design strategy. Individual mathematical modeling of key parameters such as volumetric error, machine working space, and static, thermal, and dynamic stiffness were conducted and supplemented with experimental analysis using a hammer impact test. These computations yield the optimal size of miniaturized machine tools with the technical information of other parameters.