Abstract: China’s trawl fisheries play a pivotal role in the nation’s marine capture industry. However, long-term intensive trawl activities have led to the decline of fishery resources, deterioration of population structure, and increased ecosystem vulnerability. Against the backdrop of tightening international fisheries governance and growing concerns over illegal fishing, there is an urgent need to shift from scale expansion to high-quality development in China’s trawl fishery. Digital technology, as a representative of new quality productive forces, offers a critical pathway for the transformation and upgrading of trawl fisheries. The present paper systematically reviews the evolution of China’s trawl fisheries through several developmental stages which are from human-dominated operations to mechanization, automation, and the current ongoing digital transformation. It provides a focused analysis of digital technology systems applied across four key segments: vessel monitoring, fishing forecasting, fishing operations, and catch handling. Vessel monitoring systems enable the identification and regulation of fishing behaviors, enhancing oversight and compliance. Fishing forecasting technologies, integrating remote sensing and artificial intelligence, have significantly improved the accuracy of fishing ground predictions. During fishing operations, the use of sensors and image recognition technologies has enhanced the capability to monitor gear status and support selective harvesting, reducing bycatch and ecological impact. In catch handling, automated sorting and traceability systems have been adopted to improve product quality and data transparency. Furthermore, this study proposes a digital twin framework for the entire trawl fishing process, comprising three core modules: virtual simulation, real-world perception, and intelligent decision-making. This system aims to achieve precise mapping and closed-loop optimization of fishing operations. Despite China’s technological advantages in areas such as the BeiDou navigation and artificial intelligence, challenges remain, including the limited localization of key underwater sensing equipment and insufficient virtual simulation capabilities. Moving forward, it is essential to strengthen data governance, achieve breakthroughs in core technologies, and enhance policy coordination to advance the trawl industry toward a data-driven, intelligently managed, and fully traceable development model.