Aging and some lifestyle habits cause plaque accumulation in the blood vessels of the heart and this causes narrowing of the arteries. Stents are tiny wire mesh tubes which are used in balloon angioplasty to keep the vessels open. However, the stented vessel has a risk of re-narrowing due to the recovery response of the stented vessel segment and this is called in-stent-restenosis. The objective of this study is classifying patients according to their risks of restenosis. For this purpose, first a utilites additives discriminates model called parametrized classification model is developed, then to improve the classification performance of this model, a non-dominated sorting based multi-objective evolutionary algorithm (NSGA-II) is implemented. Finally, computational experiments are conducted with real life data to demonstrate the efficiency of proposed methods.