 This study used a combination of machine learning algorithms and environmental data to create a model that can accurately predict the future distribution of different types of biomes across the globe. The model was trained on 8,959 training points from the Biome 6000 dataset and then tested against three different climate change scenarios. The results showed that increasing temperatures and decreasing precipitation levels would lead to significant changes in the distribution of certain biomes, such as tropical forests and tundras. These changes could have major implications for biodiversity and ecosystem services. This article was authored by Carmelo Bonanella, Tomaslav Hengel, Leandro Parente and others.