Pathfinding is a foundational system within the game development industry, enabling intelligent agents to navigate dynamic and complex environments efficiently. As games have evolved, the need for faster and more scalable algorithms has become critical for maintaining immersion and realism. This paper explores several existing pathfinding algorithms, focusing on the strengths and limitations of foundational methods such as Dijkstra’s and A*, and examines modern optimizations including Goal Bounding and Jump Point Search (JPS). These methods, when combined, offer substantial performance improvements, particularly for large static maps used in modern games.