Virtual reality (VR) and explainable artificial intelligence (XAI) have potential applications in cardiology, particularly in enhancing techniques for diagnosing and treating cardiac disease. This study aims to investigate how transparent artificial intelligence (XAI) decision-making processes, in conjunction with the immersive visualization capabilities of virtual reality (VR), can enhance medical diagnosis and treatment plans for various cardiac issues in terms of precision, effectiveness, and comprehensibility. Giving cardiologists and medical students access to interactive virtual reality environments with XAI-provided explanations aims to demonstrate improvements in diagnosis accuracy and treatment choices’ efficacy. The strategy includes developing virtual reality scenarios for therapy planning and heart disease diagnostics, and XAI is utilized to explain AI decision-making. Pre- and post-tests will be administered to participants, including cardiologists and medical students, to assess the impact on their capacity to diagnose patients and comprehend treatment plans. To assess perceived advantages and user satisfaction, qualitative data will also be gathered through surveys and interviews. Increased diagnostic accuracy, better transparency in AI decision-making, and better cardiac education tools are some of the expected advantages of this research. The findings might have a big impact on how VR and XAI technologies are applied in medicine, which could lead to better cardiac patient outcomes in the long run.