1.  Permutations and Combinations: If the problem asks for all possible ways to arrange or select items, backtracking is often a good approach.
2.  Constraints Satisfaction: Problems that involve placing items under certain constraints (like Sudoku, N-Queens) are often solved with backtracking.
3.  Exploring All Paths: If the problem involves exploring all possible paths or sequences (like in a maze or grid), backtracking can be useful.
4.  Partial Solutions: When a problem can be solved by building a solution incrementally and requires “un-choosing” decisions, backtracking is usually applicable.

1.  Pruning: Cut off branches of the search tree that cannot lead to a valid solution to reduce the search space.
2.  Memoization: Store the results of previously computed subproblems to avoid redundant calculations.
3.  Greedy Choices: Sometimes, making greedy choices combined with backtracking can lead to faster solutions.