Convolutional Neural Networks (CNNs) are deep learning algorithms that facilitate the processing and analyzing visual data, such as images and videos. The interpretation and validation of CNN –generated results work as an important tool to assist with imaging modalities and outcome prediction to augment the wide and varied expertise the physicians, skilled clinicians, pediatric cardiologists, and healthcare professionals bring to this effort. Given the heightened risk of arrhythmias and heart failure among patients with coronary heart (CHD), the potential of AI algorithms to predict these conditions holds immense potential as a life-saving tool. Early accurate detections can facilitate timely diagnosis of conditions like congenital heart diseases in neonates and infants, and in areas with limited or no access to quality diagnostics, an initial AI report can go a long way in helping a General Practitioner address the issue effectively and efficiently. In recent years, AI-based solutions in pediatric heart care have delivered significant benefits, including early detection of heart abnormalities, and timely interventions enabling non-cardiac doctors and general practitioners to create the Golden Hour for pediatric cardiologists to address potential issues.