The Future Market is becoming increasingly important in the global scenario of Corporate Finance. The main interest in this segment of finance is the need of being protected against the volatility of financial markets. Accordingly, one of the most traded commodity is oil. Because of difficulty in determine the value of future contracts on oil barrel, many models were created to demonstrate the evolution of their prices over time. The use of stochastic processes to represent possible trajectories of the time series is reaching more and more notoriety because it incorporates the randomness in the analysis. This study seeks to test the effectiveness of the proposed model in predicting the price of future contracts one step ahead, i.e. to estimate the price for a certain date on the preceding date. Consequently, the objective of the study is consistent with the primary objective of time series analysis that is to build models capable of forecasting. Furthermore, it will be estimated the spot price, variable that is not observable in the market, then the values obtained will be faced with a proxy. The spot price is useful for traders who need to obtain the value of an asset that is not transacted in this way at the exchange. Estimates of the parameters of stochastic processes will be made through a statistical tool that has become widely used in financial models, the Kalman filter. The procedure is to adopt well known model of stochastic process for a series of prices of commodity futures contracts, estimating its parameters and state variables with the filter, using it to forecast the prices of future contracts and to estimate the spot price, and later comparing the estimates and the real values collected from the market. Thus, it will be evaluated ability of the model to fit the new structural changes in the time series. The tools will always be explained in an accessible way, demonstrating each step and where possible making parallel with other more basic knowledge.