This large database study of resonant magnetic perturbation (RMP) edge localized mode (ELM) suppression thresholds in the AUG, DIII-D, EAST, and KSTAR tokamaks details the key strengths and weaknesses of RMP metrics. The RMP ELM suppression database used for this work contains plasma information at the time of transition from ELMing to ELM suppressed states where a clear experimental threshold is identified. The experimental threshold distributions are compared for five metrics: (1) the island overlap width, (2) pedestal top Chirikov overlap, (3) peeling edge displacement, (4) pedestal top resonant drive, and (5) edge dominant mode overlap. The distributions, the regularity of the dependence on RMP coil currents, and the sensitivities of a given metric to equilibrium reconstruction details are compared. The overlap metric proves to be a good compromise between including the appropriate plasma response physics and maintaining a numerical robustness. This quantity does not exhibit clear power-law scalings for projection, but machine learning can assist in predicting thresholds within the existing parameter ranges and providing uncertainty quantification of those predictions. Two new first-principles models, one utilizing a threshold from the non-linear Modified Rutherford equation evaluated at the pedestal top and one utilizing the SLAYER code to calculate the linear tearing threshold from torque balance, offer possible paths to extrapolation beyond the existing database parameter space.