In the present paper, in order to model rough honing operations, statistical regression correlation models are presented for surface roughness and material removal rate as a function of process variables. Several different models were studied: linear, quadratic, exponential, etc. In addition, Box-Cox transformations were performed to the models so as to improve their fit. Models were compared taking into account two different criteria: R2(Adjusted) coefficient and R2(Predicted) coefficient. Reduced second order models with Box-Cox transformations were found to be appropriate for modeling average roughness and reduced first order models with Box-Cox transformations for modeling material removal rate.