Phonocardiogram (PCG) signal is a particular approach to explore cardiac activity, to develop technics that may serve medical staff to diagnose several cardiac diseases. We took advantage of PCG signal that shows heart murmurs on its tracing dissimilar to other cardiac signals, to design an algorithm to study and classify heart murmurs. In this paper, the importance is given to the severity of murmurs to highlight its impact, since depending on its stage the patient could be in life-threatening point; therefore, the purpose of this paper is focused on three essential steps: according to the algorithm, extracting murmurs and classifying them to deferent stages then investigate the impact of severity on cardiac frequency through some parameters. The severity stage calculation was based on energy ratio (ER) which is recommended by recent studies as an effective factor, however, we succeed to validate that murmur energy (ME) is also a qualified feature to determine severity. But despite that murmur duration, it's an inefficient way to judge the cardiac severity, which is a very important indicator of the general health of the human body. This study is done on considering many patients and it reveals very interesting results.