Sensitivity analysis in linear programming helps industrial engineers make decisions by assessing how variations in input parameters, such demand, costs, or resource availability, impact the best possible outcome. By identifying important restrictions and variables that have the biggest effects on results, it assists engineers in understanding how resilient their solutions are. Decision-makers can plan for uncertainties, modify resource allocations, and make well-informed decisions that reduce risks by examining how sensitive a solution is to changes in these parameters. This is particularly helpful in dynamic industrial settings where changes in supply or costs can have a big impact on logistics, production schedules, and system efficiency as a whole.