This paper introduces a heuristic repair method for solving large-scale constraint satisfaction and scheduling problems. The method starts with an inconsistent assignment and searches for repairs using the *min-conflicts heuristic*, which aims to minimize the number of constraint violations at each step. The approach is demonstrated to be significantly more efficient than traditional backtracking techniques on the *n*-queens problem, solving the one million queens problem in less than four minutes. The method is also applied to a scheduling application for the Hubble Space Telescope, showing successful performance. Theoretical analysis explains why the method works well on certain problems and predicts its effectiveness. Empirical results on the *n*-queens problem, graph-coloring problems, and scheduling applications support the method's effectiveness, highlighting its advantages over traditional methods in terms of efficiency and simplicity.This paper introduces a heuristic repair method for solving large-scale constraint satisfaction and scheduling problems. The method starts with an inconsistent assignment and searches for repairs using the *min-conflicts heuristic*, which aims to minimize the number of constraint violations at each step. The approach is demonstrated to be significantly more efficient than traditional backtracking techniques on the *n*-queens problem, solving the one million queens problem in less than four minutes. The method is also applied to a scheduling application for the Hubble Space Telescope, showing successful performance. Theoretical analysis explains why the method works well on certain problems and predicts its effectiveness. Empirical results on the *n*-queens problem, graph-coloring problems, and scheduling applications support the method's effectiveness, highlighting its advantages over traditional methods in terms of efficiency and simplicity.