This paper investigates the critical issue of marine litter in the Gulf of Aqaba, a key marine ecosystem in the Red Sea known for its rich biodiversity and economic significance to tourism and fishing industries. It emphasizes the vulnerability of this semi-enclosed body of water to various types of marine litter, including plastic waste and discarded fishing gear, posing significant threats to marine life through ingestion and entanglement. To address the limitations of traditional monitoring methods, the study proposes the innovative use of Artificial Intelligence (AI) technologies, such as machine learning and computer vision, to enhance the detection, quantification, and categorization of marine debris. The paper aims to develop an advanced prototype for underwater image analysis using AI, designed to significantly contribute to environmental preservation efforts by providing efficient, real-time assessments of marine litter in the Gulf of Aqaba, demonstrating the potential of AI to transform marine conservation strategies.