When analyzing algorithms, understanding merge sort time complexity is essential for grasping how efficiently it handles data. Merge sort is a divide-and-conquer algorithm that splits the array into halves, sorts them, and merges the sorted halves. Its time complexity is O(n log n) in all cases—worst, average, and best—making it highly efficient for large datasets. Unlike quicksort, which may degrade to O(n²), merge sort maintains consistent performance. However, it does require extra space, which is a trade-off in some applications. Knowing its complexity helps developers choose the right sorting algorithm for the task at hand.