In this study, conducted at the Laboratório de Sistemas e Tecnologia Subaquática (LSTS), we tackle the limitations of traditional hydrodynamic modelling approaches by introducing the CFD–HEKF Integrated Modelling and Estimation (CHIME) methodology. The framework derives all hydrodynamic coefficients solely from simulation data, eliminating the need for experimental trials. The approach combines high-fidelity Computational Fluid Dynamics (CFD) simulations with a nonlinear Hybrid Extended Kalman Filter (HEKF) estimator. First, six-Degree-of-Freedom (6 DoF) steady-state CFD simulations of the ISURUS AUV were performed using ANSYS Fluent to extract drag, lift, and fin derivatives. Added-mass coefficients were then calculated through transient simulations using dynamic mesh under free oscillation in three modes. Subsequently, diving and turning manoeuvres were simulated, and the resulting states were input into a MATLAB-based HEKF estimator to estimate unknown damping and added-mass terms. A mesh sensitivity analysis determined that a medium grid (~500,000 cells) provided the optimal trade-off between accuracy and computational cost. Turbulence modelling confirmed that the k–kl–ω model effectively captured laminar-to-transitional regimes. The CFD-derived hydrodynamic coefficients and HEKF-estimated results were benchmarked against analytical and experimental results from the literature. The results reveal that CFD-derived drag, lift, and fin coefficients are within 2% error of experimental values, while added-mass coefficients showed significant improvement over analytical methods. The manoeuvre results, including circular path, tactical diameter, yaw, pitch, and depth, matched field trials within 1-3% error. In contrast, MATLAB simulations using analytical coefficients consistently performed worse. The HEKF-based results demonstrated alignment of states and trajectory within 3% error of CFD results, with a maximum of 10% error of experimental results. The CHIME methodology offers a simulation-only, high-accuracy alternative for full hydrodynamic characterisation of axisymmetric AUVs. The approach provides a streamlined, cost-effective foundation for improving onboard state estimation and integrating it into real-time navigation and control systems.