Nowadays, flying is a fundamental part of society. Traveling is increasingly accessible, which feeds not only the aeronautical industry but also, for instance, the tourism sector in some regions. However, despite its importance in society in general, leading to more and more airplanes in the air, the aviation industry also becomes one of the primary sources of pollution, and when considering leisure aviation the problem becomes even more complicated. So in recent years, all aeronautical manufacturers have been working on solutions that reduce the sector's impact on climate change. Landings are of particular importance in the fuel consumption aspect, especially if it's taken into account that for various reasons a pilot may decide to abort the maneuver, being a few more kilos of fuel that will be consumed and consequently made more pollution. The present work, based on a set of algorithms, intends to propose an architecture that based on the history of successful landings from, for instance, ADS-B tools, provides the pilot suggestions, in order to reduce the probability of a go-around.