ABSTRACT Evapotranspiration is one of the most important elements of the hydrological cycle. Estimation of evapotranspiration is imperative for eff ective forest, irrigation, rangeland and water resources management as well as to increase yields and for better crop management. This study uses Surface Energy Balance Algorithm for Land (SEBAL) in estimating evapotranspiration and crop coefficient of different crops in Sidama region of Wondogenet Woreda, Ethiopia. The Landsat 8 satellite image of January 29th 2018 was used to acquire the coefficients of the respective bands. Then, the net radiation flux on the earth’s surface and the earth’s heat flux is obtained using incoming-outgoing radiation fluxes from albedo, surface emissivity coefficients, land surface temperature, and plant indicators. Next, the sensible heat flux is calculated by determining the hot and cold pixels under consideration via the atmospheric stability conditions. Finally, evapotranspiration maps are plotted. The crop coef f icient of major crop is also estimated with the respected maps being plotted. To validate the outcomes from the SEBAL algorithm, experimental methods were employed to calculate the evapotranspiration values and evaluated using suitable performance metrics. The results showed that the SEBAL generated evapotranspiration values are in high agreement with the FAO Penman-Monteith method registering the highest correlation and the lowest error. Moreover, the crop coefficients estimated using SEBAL also manifested an acceptable correlation with all methods. The outcomes show that since the performance of the SEBAL algorithm in estimating the actual evapotranspiration and crop coefficient using Landsat 8 satellite images is acceptable, the SEBAL algorithm could be a very convenient method. Moreover, it could easily be assimilated into farming management systems and precision agriculture for better decision-making and higher yield.