Non-Gaussianity index (lambda) is a new index of heart rate variability (HRV) that characterizes increased probability of the large heart rate deviations from its trend. A previous study has reported that increased lambda is an independent mortality predictor among patients with chronic heart failure. The present study examined predictive value of lambda in patients after acute myocardial infarction (AMI). Among 670 post-AMI patients, we performed 24-h Holter monitoring to assess lambda and other HRV predictors, including SD of normal-to-normal interval, very-low frequency power, scaling exponent alpha(1) of detrended fluctuation analysis, deceleration capacity, and heart rate turbulence (HRT). At baseline, lambda was not correlated substantially with other HRV indices (|r| < 0.4 with either indices) and was decreased in patients taking beta-blockers (P = 0.04). During a median follow-up period of 25 months, 45 (6.7%) patients died (32 cardiac and 13 non-cardiac) and 39 recurrent non-fatal AMI occurred among survivors. While all of these HRV indices but lambda were significant predictors of both cardiac and non-cardiac deaths, increased lambda predicted exclusively cardiac death (RR [95% CI], 1.6 [1.3-2.0] per 1 SD increment, P < 0.0001). The predictive power of increased lambda was significant even after adjustments for clinical risk factors, such as age, diabetes, left ventricular function, renal function, prior AMI, heart failure, and stroke, Killip class, and treatment ([95% CI], 1.4 [1.1-2.0] per 1 SD increment, P = 0.01). The prognostic power of increased lambdafor cardiac death was also independent of all other HRV indices and the combination of increased lambda and abnormal HRT provided the best predictive model for cardiac death. Neither lambda nor other HRV indices was an independent predictor of AMI recurrence. Among post-AMI patients, increased lambda is associated exclusively with increased cardiac mortality risk and its predictive power is independent of clinical risk factors and of other HRV predictors.