Artificial Intelligence (AI) has revolutionized scientific research, enabling data-driven discoveries and accelerating breakthroughs across various domains. This review explores the latest advancements in AI for Science, highlighting key methodologies, applications, challenges, and future directions. AI has been instrumental in fields such as physics, chemistry, life sciences, environmental studies, and astronomy. By integrating deep learning, reinforcement learning, and generative models, AI has enhanced scientific computation, hypothesis generation, and automated discovery. This paper provides a systematic review of AI-driven scientific methodologies and their transformative impact on modern research.