In Turkey, due to its geological and geomorphological structure and its climatic features, it frequently encounters natural disasters that lead to loss of life. Artvin is one of the most frequently experienced natural disasters in Turkey. Landslides triggered by extreme rainfall and natural disasters of meteorological character, especially floods, are frequently observed throughout the province, causing casualties. These natural disasters are mostly concentrated in the districts of Arhavi, Hopa and Borcka. Finally, floods and landslides occurred in arhavi, Hopa and Borcka districts due to heavy rainfall on 24 August 2015, resulting in 11 people killed and 19 injured, 6 of them from landslides. In this project, it is aimed to produce flood and landslide sensitivity maps of Ardanuç, Şavşat and Yusufeli districts of Artvin province. Two powerful machine learning approaches, the decision tree (DT) and the Support Vector Machine (SVM), will be used to assess landslide and flood sensitivity. Sensitivity analysis elevation, slope, aspect, plan and profile curvature, lithology, land use/cover, topographic moisture index topographic wetness index – TWI), stream Power Index stream power index (SPI), drainage density, rainfall, proximity to road networks and drainage parameters will be used.