To address the complex mechanical properties of coastal clay encountered during artificial ground freezing construction in coastal regions, this study investigates coastal clay by conducting mechanical tests under various freezing temperatures and confining pressures. The variations in peak strength, elastic modulus, and shear strength parameters of the frozen coastal clay were systematically analyzed. The results indicate that the peak strength and elastic modulus of the coastal clay exhibit a clear upward trend with approximately linear increases in confining pressure and temperature. A damage constitutive model for frozen soil was established, accounting for the coupled effects of temperature and confining pressure. Furthermore, a Physics-Informed Neural Network (PINN), incorporating the constitutive equations as physical constraints, was introduced to achieve the inversion and prediction of model parameters. The results demonstrate that the PINN model exhibits excellent predictive accuracy, with the coefficient of determination (R²) reaching 0.8513 under uniaxial compression and 0.9689 under triaxial compression. Compared with traditional empirical models, the PINN model reduces the prediction error of the elastic modulus to 8.96% (at 0 MPa) and 4.79% (at 0.8 MPa), demonstrating superior generalization capability. This study provides a reliable theoretical basis and parameter guidance for frozen soil construction in coastal regions.