aspg-18-2071-1792025543 20261015005223 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Journal of Intelligent Systems and Internet of Things JISIoT 2769-786X 2690-6791 2023 9 2 Mustafa Nazar Dawood Computer Technologies Engineering, Al-Turath University College, Baghdad, Iraq Mohammed Ayad Alkhafaji Department of Medical Devices Engineering Technologies, National University of Science and Technology, Dhi Qar, Nasiriyah, Iraq Ahmed Hussian Medical instruments engineering techniques, Al-farahidi University, Baghdad, Iraq Hussein Alaa Diame Technical Computer Engineering Department, Al-Kunooze University College, Basrah, Iraq Naseer Ali Hussien Information and Communication Technology Research Group, Scientific Research Center, Al-Ayen University, Thi-Qar, Iraq Sahar Yassine Department of Applied Data Science, Noroff University College, Kristiansand, Norway Venkatesan Rajinikanth Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai 602105, India Risk Management is an important task that helps to monitor the business application to eliminate the political, financial, cultural, and social consequences. The organization's risk decision is affected by several characteristics, such as lack of accountability and risk decision-making. The difficulties are resolved by applying the Machine-Learning related Business Decision Making Approach (ML-BDMA). The created framework helps to reduce the difficulties in decision-making while managing the organization's risk. The Business Decision Making process works along with the Optimistic Predictive Techniques (OPT) that are used to identify the risk which leads to attaining the business objective. This process categorizes the risk according to the qualitative characteristics of business data. The system's effectiveness was evaluated using the experimental result in which the system ensures a 98.93% performance rate, 92.25% reliability rate, 93.47% authenticity rate, 91.11% risk management rate, and 97.77% development rate while making a business decision. 2023 51 64 2071 https://creativecommons.org/licenses/by/4.0/ 10.54216/JISIoT.090204 https://americaspg.com/journal/18/article/2071 https://americaspg.com/storage/31694789135.pdf