It is found in this research to adopt a new classifier for diagnosing Cardiac Arrhythmias depending on detecting the Electrocardiograph (ECG), where the classifier can identify heart beats and extract its features. Using these features we can decide if the heart beat is healthy or disordered. Beside detection normal heart beats, the research focused on detection two diseases: 1. Premature Ventricular Contraction PVC. 2. Premature Atrial Contraction PAC. The new classifier diagnosed the two diseases with a very high quality where the accuracy average is 97.56%. The new classifier is developed depending on algorithms of ANFIS Adaptive Neural Fuzzy Inference System. System includes two consecutive neural networks; first one sorts the heart beats to two types: normal and abnormal were the second diagnose the disease of the disordered heartbeats only. This new classifier offered higher levels of efficiency and accuracy in the comparison with the internationally known classifiers.