It is well known the number of passengers per month on the airports, is highly linked to the seasons of the year. Usually in summer, the people use to travel more because their vacations, likewise during the xmas days and winter holidays. This periodicity on the curve makes the Recurrent Neural Network (RNN) algorithm works very well when is asked to forecast the passengers revenue for future months. From this perspective, by using data from SABRE , we were capable of calculate the number of passengers travelling through all the European airports, and with this information was posible to estimate the demand evolution on every airport in the EU. As an example, the plots below shows the time evolution of the total passengers traffic on Europa (top) and in the London Heathrow (bottom). Note when we study a single airport the curve becomes a little more noisy, however the RNN shows a RMSE > 0.8 (:O!).