Stock market prediction poses a significant challenge due to the uncertain behavior, complicated pattern, and volatility of the market. The electric vehicle market is one of the most volatile and rapidly growing markets today. EV stock prediction presents different challenges compared to traditional stocks due to factors such as technological advancements, supply chain dynamics, supporting infrastructures, geopolitics, and sustainability trends. In this paper, we explore the distinct drivers of EV stock performance, compare them with traditional methodologies, and highlight the need for specialized approaches to account for EV sector’s unique characteristics and uncertainties. We proposed a framework that predicts the EV stock price that uses BiLSTM networks integrated with Explainable AI techniques with SHAP. XAI helps to bring trust and clarity among the stakeholders and aids in making accurate decisions. BiLSTM handles past and future data and captures complex temporal dependencies.