Explainable artificial intelligence (XAI) is a method to understand “Why and How “outcomes created by machine learning algorithms are useful and applicable. Explainable AI describes an AI model, its significance and impact. It helps characterize model accuracy, fairness, transparency and outcomes in AI-powered decision making. As most of the ML/DL algorithms are experimented for various application, there is importance of justification of its outcomes. Explainable AI will add value to the research carried out in this area. Virtual: https://events.vtools.ieee.org/m/377915