Abstract: When designing the waterproofing and drainage system for an subsea tunnel, it is crucial to have a clear understanding of the surrounding rock's inherent water-blocking capabilities to achieve active control over the drainage volume. This paper first introduces the concept of the surrounding rock impermeability, defined as the ability of the tunnel's surrounding rock to resist water infiltration. A predictive formula for water inflow under nonlinear seepage conditions in fractured rock masses is derived, revealing the mechanisms by which factors such as engineering geological conditions, hydraulic connectivity, and tunnel size effects influence the impermeability of the surrounding rock. On this basis, a statistical analysis of water inflow data from 52 typical underwater and water-rich tunnel sections identifies key factors influencing the impermeability of tunnel surrounding rock. The key factors are including rock cover thickness, hydraulic head, uniaxial saturated compressive strength of the rock, and volumetric joint count. These factors are used as indicators to establish a classification standard for the rock impermeability. By applying the bisection method and the information gain ratio from the training dataset, a machine learning approach has been used to analyze the statistical data. A decision tree model capable of analyzing continuous-valued attributes was established, enabling the classification of the surrounding rock impermeability based on relevant rock parameters. Finally, the model was applied to the drill-and-blast section of the Qingdao-Jiaozhou Bay Second Subsea Tunnel, verifying the rationality and feasibility of the proposed anti-seepage classification method. The research findings provide a theoretical basis for determining drainage control standards in subsea tunnels. Compared to traditional rock mass classification methods, the anti-seepage classification method comprehensively considers the conditions of the surrounding rock and its seepage mechanical response, leading to a more scientific and reasonable approach to waterproofing design and zoned drainage strategies.