To assess the value of background continuity and amplitude fluctuations of the EEG for the prediction of outcome of comatose patients after cardiac arrest. In a prospective cohort study, we analyzed EEGs recorded in the first 72 h after cardiac arrest. We defined the background continuity index (BCI) as the fraction of EEG not spent in suppressions (amplitudes < 10 µV for ≥ 0.5 s), and the burst-suppression amplitude ratio (BSAR) as the mean amplitude ratio between non-suppressed and suppressed segments. Outcome was assessed at 6 months and categorized as "good" (Cerebral Performance Category 1-2) or "poor" (CPC 3-5). Of the 559 patients included, 46% had a good outcome. Combinations of BCI and BSAR resulted in the highest prognostic accuracies. Good outcome could be predicted at 24 h with 57% sensitivity (95% confidence interval (CI): 48-67) at 90% specificity (95%-CI: 86-95). Poor outcome could be predicted at 12 h with 50% sensitivity (95%-CI: 42-56) at 100% specificity (95%-CI: 99-100). EEG background continuity and the amplitude ratio between bursts and suppressions reliably predict the outcome of postanoxic coma. The presented features provide an objective, rapid, and reliable tool to assist in EEG interpretation in the Intensive Care Unit.