Explainable Sorting Models is a formal framework in algorithmic decision-making that characterizes sorting mechanisms designed to provide human-interpretable justifications for their ordering outputs, distinguishing them from conventional sorting models by explicitly incorporating transparency and post-hoc interpretability into the sorting process.