Nowadays, the automotive industry has attracted the attention of consumers, and product quality is considered as an essential element in current competitive markets. Security and comfort are the main criteria and parameters of selecting a car. Therefore, standard dataset of CAR involving six features and characteristics and 1728 instances have been used. In this paper, it has been tried to select a car with the best characteristics by using intelligent algorithms (Random Forest, J48, SVM, NaiveBayse) and combining these algorithms with aggregated classifiers such as Bagging and AdaBoostMI. In this study, speed and accuracy of intelligent algorithms in identifying the best car have been taken into account.