The prognostic value of heart rate variability in patients with dilated cardiomyopathy (DCM) is limited and does not contribute to risk stratification although the dynamics of ventricular repolarization differs considerably between DCM patients and healthy subjects. Neither linear nor nonlinear methods of heart rate variability analysis could discriminate between patients at high and low risk for sudden cardiac death. The aim of this study was to analyze the suitability of the new developed segmented Poincaré plot analysis (SPPA) to enhance risk stratification in DCM. In contrast to the usual applied Poincaré plot analysis the SPPA retains nonlinear features from investigated beat-to-beat interval time series. Main features of SPPA are the rotation of cloud of points and their succeeded variability depended segmentation. Significant row and column probabilities were calculated from the segments and led to discrimination (up to p<0.005) between low and high risk in DCM patients. For the first time an index from Poincaré plot analysis of heart rate variability was able to contribute to risk stratification in patients suffering from DCM.