It is generally accepted that Micro and Small Enterprises (MSEs) have significant contributions to job creating, generating income, and poverty alleviation. However, the performance of MSEs in Enarj Enawga Woreda is low. So, this study was done to investigate the determinants of MSE’s performance in the woreda using descriptive statistics and an econometric model of logistic regressions. The main objective of the study was to find out the determinants of Micro and Small Enterprise’s performance in terms of employment and profit. More primary and some background secondary data were employed in getting the necessary information for the analysis of the study. A total of 181 sample respondents were identified using the multiple-stage sampling technique. The result of the study shows that the majority of the MSEs have been a recent establishment and faced challenges of inadequate startup capital, limited access to credit, government policies and regulation related factors, unfair competition, limited infrastructure facility, lack of training, and lack of know-how and skills to use technology. Furthermore, the study also noted that most of the operators were found to be young labor force of male operators with educational qualification of high school or less. The study used profit and employment as performance or growth indicators. Profit calculated as the total sales revenue minus annual total costs and employment measured as the natural logarithm of current employment minus the natural logarithm of initial employment and dividing by age of the enterprise. After calculating, Micro and Small Enterprises were grouped into two categories good and low performance. Micro and Small Enterprises which had growth rate ≤ 0 categorized into low performance and MSEs which had growth rate > 0 are good performance. The findings of the study show that out of the total sample 40.88% of MSEs have low performance and 59.12% of MSEs have good performance in terms of profit and 49.17% of MSEs have low performance and 50.83% of MSEs have good performance in terms of employment. The result of logistic regression analysis shows that out of 13 determinant variables 10 variables; age of the operator, age of the enterprise, amount of initial capital, access to raw material, market competition problems, government policies and regulation problems, access to training, education level of the operator, access to modern technology, and access to market factors revealed statically significant to affect performance of MSEs in terms of profit. Whereas out of 12 explanatory variables 6 variables namely government policies and regulation problems, access to modern technology, infrastructural related problems, prior experience of the owners, ownership of work premises and access to credit factors revealed statically significant to affect the performance of MSEs in terms of employment. Therefore, attention should be given by the policy makers and other concerned bodies to develop supportive programs and corrective measures to ease the constraints and difficulties facing performance of MSE.