This research aimed to critically analyze the determinants of technology adoption and the use intensity by small farm households in the study area (Masha District). Six kebeles were randomly selected from the district, and 251 sample households were proportionally and randomly identified from the selected kebeles. The data collected from the sample households have been analyzed using both descriptive as well as inferential analysis. For inferential analysis, the Double Hurdle Model was adopted to estimate the technology adoption decision as well as use intensity of small farm households in the study area.  The findings show that technology adoption decisions were associated with household-specific characteristics such as sex, education, extension, and family size, increasing the likelihood of technology adoption. In contrast, the age of the household head has a negative contribution to it. On the other hand, institutional factors such as access to extension service and access to credit facilities have a significant impact where the latter has contributed negatively to the farmers’ decision regarding technology adoption.