Quantum computing is a rapidly evolving field that harnesses the principles of quantum mechanics to revolutionize computational power. This research article explores the potential implications of quantum computing in finance, with a specific focus on its applications in portfolio management. The investigation begins by exploring the fundamentals of quantum computing, including qubits, quantum gates, measurement, and entanglement. Subsequently, the article investigates the potential applications of quantum computing in portfolio management, such as optimizing asset allocation, enhancing risk modeling techniques, and improving decisionmaking processes. Through a comprehensive review of the current state and future prospects, the research evaluates the feasibility, challenges, and anticipated impact of quantum computing in the financial industry. The research findings indicate that quantum computing has the potential to significantly enhance portfolio management strategies. By leveraging the computational power of quantum computers, optimization problems in asset allocation can be addressed more efficiently compared to classical methods. Risk modeling and analysis can also benefit from quantum computing, with improved accuracy in risk assessments, stress testing, and Value at Risk (VaR) calculations. Quantum computing's ability to process large datasets and provide probabilistic outcomes can aid decision-making processes in portfolio management, leading to more informed investment decisions. However, the current state of quantum computing in finance is still primarily experimental, with challenges such as error correction, scalability, and the lack of standardized software tools that need to be overcome for practical implementation. The implications of quantum computing extend beyond portfolio management to areas such as derivative pricing, encryption methods, and machine learning in finance.