Automotive industry is constantly developing due to the use of new technologies and materials that are allowing the finding of novel solutions in order to solve existing problems. This study is focused on using a mathematical predictor called Kriging for the tribological properties of iron-based composites so as to estimate their values. First, experimental data regarding the tribological properties was obtained for four Fe-Cu-graphite-Ni-TiO₂ composite materials. Based on this data the appropriate Kriging estimator is established and the values for the friction coefficient and wear rate are predicted at intermediary TiO₂ contents. Therefore, without using expensive equipment and time-consuming experimental tests such as trial and error method, the tribological properties of iron-based composite materials can be estimated. Based on the predicted values and using an optimization algorithm, the material with the optimal tribological behavior can be determined in order to be used in applications for the automotive industry, such as the manufacturing of brake pads.