Climate change is one of the most pressing challenges of the 21st century, with far-reaching implications for ecosystems, economies, and human societies. Accurate prediction of global climate patterns is essential for mitigating its impacts and informing policy decisions. This paper explores the integration of artificial intelligence (AI) and data science with environmental science to enhance climate change modeling. By leveraging machine learning algorithms, big data analytics, and advanced computational techniques, AI-driven models offer unprecedented accuracy and scalability in predicting climate trends. This study reviews the methodologies, applications, and outcomes of AI-driven climate modeling, highlighting its potential to revolutionize our understanding of climate systems. The findings underscore the importance of interdisciplinary collaboration in addressing the complexities of climate change.