Abstract: Heart Rate Variability (HRV) can be measured with the variation of RR intervals exhibited in a sequence of ECG sample. For a short-term HRV, measuring time is usually defined. However, with numerous possibilities of shortening the measuring time to evaluate the HRV further precision can be exhibited. This paper elucidates on analyzing raw ECG data and then further pre-processing it to obtain a smoothened data to detect mean HRV value .Further the ECG Data subsets of different age groups is taken and analyzed to find out the implications HRV has in patient’s lives and as a predictor of mortality. Heart rate variability (HRV) has been a strong predictor of heart failure and its prognostic significance is yet to be explored. The data in the experiment are taken from publically available source physionet.