Abstract: Anchorage saturation is a core indicator for evaluating the utilization status of port anchorages, directly affecting port navigation safety and operational efficiency. However, existing calculation methods often fail to account for the actual anchoring requirements of vessels with different lengths, resulting in considerable deviations from real operating conditions and making it difficult to accurately reflect actual anchorage utilization. To address this problem, this study proposes an Automatic Identification System (AIS) data-driven model for calculating anchorage saturation. First, preprocessed AIS data of anchored vessels are classified according to ship length, and the standard ship length for each interval is determined. Then, the anchoring circle area corresponding to the standard ship length in each interval is calculated. Finally, the theoretical capacity of the anchorage is estimated based on the proportion of standard ships, the anchoring circle area, and the total anchorage area, thereby establishing an anchorage saturation calculation model for different ship-length intervals. Case studies are conducted using AIS data from seven anchorages around Jiaozhou Bay, Qingdao Port, with three anchorage area utilization rates of 0.6, 0.7, and 0.8 set for empirical validation. The results show that for each 0.1 increase in the anchorage area utilization rate, the overall estimated saturation decreases by approximately 5 percentage points. Compared with the traditional single representative ship-type method, the proposed model produces more stable calculation results, which are highly consistent with feedback from maritime authorities and port operators. These findings indicate that the proposed model can accurately reflect the actual utilization status of port anchorages and provide technical support for anchorage planning and management, optimal allocation of anchorage resources, and future smart port construction.