Sensitivity analysis is a technique used to determine how different values of an input variable can impact a model's output. By changing one variable at a time while keeping others constant, analysts can identify which factors have the most influence on results. This is particularly useful in fields like finance, engineering, and environmental science. The results of sensitivity analysis help decision-makers understand the robustness of their models and the potential risks involved. For example, in financial modeling, knowing how sensitive a project's profitability is to changes in interest rates can guide investment decisions and risk management strategies.