The Upper Blue Nile Basin (UBNB) in Ethiopia has a huge hydropower development potential and it covers a considerable amount of the present hydropower consumptions in the country. However, as hydropower is basically rainfall-dependent, its future sustainable utilization under climate change is highly uncertain. As a result, it is critical to identify the amount of wind energy that can be harnessed in the area since wind is a good substitute for hydropower. Nonetheless, wind energy suitability studies and potential estimations are rarely researched in the UBNB. The objective of this study is, therefore, to investigate wind farm suitability based on a multi-criteria decision method using Geographic Information System (GIS) and to determine the energy potentials of those suitable areas in UBNB. Wind speed, slope, land use/land cover, distance from grids, roads, urban areas, and protected areas were considered to identify suitable wind farm sites. The relative weights of these factors were calculated and overlaid by the principle of pairwise comparison in the context of the Analytic Hierarchy Process. From the total area it was found that 1498.69 km2 was highly suitable. The suggested highly suitable areas for wind farm sites fall in the northeastern part of the study area. For wind power potential investigation, wind speed data of ten sites with 15 min intervals of four years (2017-2020) were accessed from National Meteorology Agency (NMA). And it was statistically analyzed using statistical methods and software like MS-Excel and MATLAB programs. The best Weibull parameters estimator was identified based on the statistical test results for each station. From the wind power density analysis using 15-minute interval wind speed, the highest wind power density was recorded in Wogeltena and Gatira with wind power density of 227.56 and 216.50 W/m2 at 50 m, respectively. Finally, the power density was higher during the dry and short rainy season and can be said that wind is a good complement to hydropower. In conclusion, most of the wind speed data in this study were not enough for wind energy potential estimations at large scales. This may be because the meteorological stations in the study area may not be located at ideal places for wind energy potential estimations. Thus, different wind speed measuring tools (i.e. taller wind mast) are suggested for additional wind energy potential investigations. Relatively, the northeastern parts of the study area are the most promising sites discovered in this study. Hence, these areas might be regarded as feasible for various wind energy applications (i.e. grid-connected and stand-alone).