This study introduces a rapid predictive method for evaluating subsonic flutter instability in low-pressure axial flow turbine blade cascades. Flutter, an aeroelastic instability, results from unsteady aerodynamic forces and blade oscillation phase differences, risking structural failure. Conventional high-fidelity CFD-coupled structural models are computationally costly, while empirical methods lack versatility for new designs, and experimental approaches demand extensive testing. The proposed method utilizes a database of aerodynamic damping and aeroexcitation data from NACA0010 airfoil cascade experiments in a subsonic wind tunnel. Aerodynamic damping coefficients are derived for varying angles of attack, inter-blade phase shifts, and reduced vibration frequencies (k). A critical reduced frequency (kcr) serves as a stability threshold, incorporating flow velocity, blade chord, and oscillation frequency. Focusing on highly loaded cascade sections (0.75–0.95 airfoil height), the method uses a functional relating angle of attack and torsional vibration amplitude, enhanced by numerical calculations. This approach minimizes reliance on costly simulations and testing, enabling efficient, reliable flutter stability assessment for early-stage turbine blade design. Supported by the Czech Science Foundation, it improves design efficiency and reliability.