This study investigated the impact of microfinance on household’s food security in Gazo district, Eastern Amhara region, Ethiopia. Microfinance is one of the most essential tools that contribute to the improvement of livelihoods through provision of financial and supporting services to the poor. There is a huge gap to bridge between the microfinance services targeted objectives and the reality that occurred in the improvement of household livelihood. The objective of this study was impacts of microfinance services on rural household food security. A total of 328 sample households were selected through stratified and random sampling in Gazo district, norh Wollo zone, Amhara region of Ethiopia in the year 2019. We used households’ calorie intake, dietary diversity and food consumption score as outcome indicators for food security. To identify determinants to micro-finance credit and saving services participation a probit model was used. The impact analysis was performed using endogenous switched regression model. On top of the econometric models, we also analyzed descriptive and inferential statistics to describe different socioeconomic characteristics of sample household. Age, age squared, education, off/nonfarm income, livestock size, market distance, extension contact and cultivated land size were significant determinant factors for the participation of households in micro-finance services. Accordingly, the outcome of endogenous switching regression model showed that the mean of daily kilo calorie intake per adult equivalent, food consumption score and household dietary diversity was higher for micro-finance participant than that of non-participants. Based on the finding, it is recommended that the microfinance institutions and other concerning bodies should work more on increasing rural households participation in microfinance services to improve the food security status of participant households .In addition, the institution should expand its outreach to the gross level of the rural areas. Key words: - micro- finance, food security, impacts, endogenous switching Regression model