aspg-1-2298-1791417666 20261008000106 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group American Journal of Business and Operations Research AJBOR 2770-0216 2692-2967 2024 11 1 Noura Metawa University of Sharjah, Sharjah, UAE Rania Itani University of Murdoch, Dubai, UAE This article presents our research effort to explore the convergence of sustainable banking practices and predictive modeling for bank loan defaults, with a primary emphasis on addressing the pressing need for resilient financial systems. To this end, an applied methodology is presented in this study to model bank loan defaults, emphasizing the incorporation of sustainability criteria into predictive analytics. Given the temporal nature of load data, our approach leverages Long Short-Term Memory (LSTM) networks as its backbone process for predictive modeling. The empirical results of the public case study underscored the enhanced predictive accuracy completed through this approach, emphasizing the pivotal function of integrating sustainability metrics in predicting mortgage defaults inside the banking area. 2024 14 18 2298 https://creativecommons.org/licenses/by/4.0/ 10.54216/AJBOR.110102 https://www.americaspg.com/journal/1/article/2298 https://www.americaspg.com/storage/articles/manuscripts/01M0EASS2TGGY86KW7DKZVW6GG.pdf