aspg-28-1448-1792155151 20261016125231 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Journal of Artificial Intelligence and Metaheuristics JAIM 2833-5597 2022 2 1 Khadija Shazly Faculty of Computer and Information, Mansoura university, Egypt Nima Khodadadi University of Miami, 1251 Memorial Drive, Coral Gables, 33146, FL, USA Credit card use is rapidly increasing as a result of the widespread availability of these cards, the ease of making electronic transfers, and the ubiquity of online shopping. But credit card debt poses a serious risk to businesses and governments alike, not to mention individual savers and investors. Consequently, the need for efficient, timely, and reliable ways to anticipate credit card risk has grown. In this study, we offer a framework that combines three classifiers, namely, support vector machines, multilayer perceptron and decision trees, to improve the network's accuracy. The proposed strategy is shown to be very competitive with others through simulation. 2022 46 54 1448 https://creativecommons.org/licenses/by/4.0/ 10.54216/JAIM.020105 https://www.americaspg.com/journal/28/article/1448 https://www.americaspg.com/storage/91673415943.pdf