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Oil distillates are considered important elements to accomplish the missions of the Argentine Air Force (AAF). Of all oil products consumed by the AAF, jet fuel is the resource with highest demand and at the end of the day the most expensive support item procured by the Argentine Air Force. Accurate predictions of Argentine jet fuel prices are necessary to improve AAF financial and logistics planning. This thesis presents a systematic, statistical regression approach to forecast Argentine jet fuel prices. The application of this methodology has allowed us to obtain avery useful model that utilizes information available on the internet to produce forecasting of jet fuel prices withaverage percentage absolute errors lower than 3%.