Fusion: Practice and Applications FPA 2692-4048 2770-0070 10.54216/FPA https://www.americaspg.com/journals/show/2097 2018 2018 Scientific Research Center, Al-ayen University, Thi-Qar, Iraq Sajad Sajad Technical Computer Engineering Department, Al-Kunooze University College, Basrah, Iraq Maryam Ghassan Majeed College of National Technical Engineering, Department of Medical Devices Engineering Mohammed Brayyich Computer Technologies Engineering, Al-Turath University College, Baghdad, Iraq Nabaa R. Wasmi Zaydan Medical instruments engineering techniques, Al-farahidi University, Baghdad, Iraq Aqeel Ali Fraunhofer IVI,85051, Ingolstadt, Germany Marwan Qaid Mohammed6 Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai 602105, India Venkatesan Rajinikanth Expanding the industrial component through investment in R&D is a crucial objective of the region's current industrial strategy. Significant research and investment opportunities must complement the effectiveness of the region's industrial policy. Few studies have attempted to understand the interactions between inter-organizational clusters and the capacity to sustain those clusters; most studies on innovation capacity focus on the business level. This article suggests using the One Belt All Road (OBAR) strategic framework to assess regional industry's cluster innovation capacity (CIC) and international trade and investment. The cluster innovation capability was developed using a theoretical framework through qualitative textual assessment. As a result, information management, diffusion, and acquisition capacity are the three primary abilities that make up the cluster innovation capacity. The degree of investment effort in the region's industrial sectors and the factors influencing corporate innovation have been found to be correlated. The research highlighted obstacles and potential remedies for encouraging creative thinking and financial backing among regional manufacturers. Compared to the current system, the suggested system (OBAR) achieves superior results in accuracy (87.6%), system dependability (94.8%), the F-1 measure (87.1%), and error rate (8.1%). 2023 2023 175 188 10.54216/FPA.130114 https://www.americaspg.com/articleinfo/3/show/2097