Nowadays and taking into account the different indicators and the forecast of the air traffic volume from Eurocontrol, it is accepted the idea that the traffic will be doubled by 2030, that is why it is so important to find new and efficient methods which allow the infrastructure absorb such a huge demand. Hence the importance of designs a plan in order to increase the actual capacity. This is the example of ATM MASTER PLAN included inside SESAR (Single European Sky and Research). The main aim of this project is to test a different tool which could lead to detect conflicts on the airspace and find which is its performance compared to a traditional 4D forecast trajectory software. It will be entirely developed on the environment of Python and the Scikitlearn library will be used in order to make the machine learn which is a conflict situation and which not.