Sensitivity Analysis explores how the uncertainty in the output of a mathematical model or system can be apportioned to different sources of uncertainty in its inputs. It reveals which Input variables most profoundly influence the Output, helping to understand robustness and inform decisions. This technique is vital in fields ranging from engineering to economics.