The paper introduces a novel technique for correcting jet measurements in high-luminosity LHC collisions to account for pileup and underlying event effects. The method, based on jet areas, is data-driven and does not rely on Monte Carlo modeling. It involves measuring the susceptibility of each jet to diffuse noise and estimating the level of this noise in each event. The correction is applied after jet finding, ensuring independence from detector setup. The technique is demonstrated for various processes, including dijet events, leptophobic $Z'$ boson reconstruction, and top quark mass reconstruction, showing significant improvement in resolution and accuracy. The method is also effective in low-luminosity LHC and heavy-ion collision scenarios, where background contamination is high. The authors conclude that their approach is simple, robust, and provides a reliable way to correct jet measurements in high-luminosity LHC data.The paper introduces a novel technique for correcting jet measurements in high-luminosity LHC collisions to account for pileup and underlying event effects. The method, based on jet areas, is data-driven and does not rely on Monte Carlo modeling. It involves measuring the susceptibility of each jet to diffuse noise and estimating the level of this noise in each event. The correction is applied after jet finding, ensuring independence from detector setup. The technique is demonstrated for various processes, including dijet events, leptophobic $Z'$ boson reconstruction, and top quark mass reconstruction, showing significant improvement in resolution and accuracy. The method is also effective in low-luminosity LHC and heavy-ion collision scenarios, where background contamination is high. The authors conclude that their approach is simple, robust, and provides a reliable way to correct jet measurements in high-luminosity LHC data.