A new computational algorithm to quantify nonlinear heart-rate dynamics was developed. The term stochastic nonlinear autoregressive (SNAR) model was coined to emphasize that the method models both the deterministic and the stochastic components of the system. Finally, the applicability and reliability of the SNAR algorithm to predict the outcome of cardiac electrophysiologic study (EPS) were demonstrated.