Microfinance has played a key role in the fight against exclusion and the promotion of entrepreneurship in developing countries. An important question today is how to increase the reach and profitability of microfinance, in a context where subsidies are withdrawing to promote the viability and sustainability of microfinance institutions (MFIs). Efficiency analysis has found favor in this context and has attracted growing interest among professionals, partners, and researchers. Abundant empirical work has been conducted over the last ten years on this subject, in very different contexts and with different methodologies. The purpose of this article is to provide a meta-regression analysis on parametric and nonparametric estimations of Mean Technical Efficiency (MTE) in microfinance, using a data set of 262 observations from 38 studies. The results show that, in the microfinance industry, MTE scores have increased over time. However, with an MTE rate of approximately 61.1%, there is room for improving efficiency. MFIs use more resources than necessary for the results achieved in terms of outreach and revenue generated. Our results show heterogeneity of MTE according to the methodological approach of the studies. Studies with a larger number of variables (inputs and outputs) produced higher MTE scores than did those with a smaller number of variables. Studies using the variable returns to scale assumption resulted in higher MTE scores than those using constant returns to scale. In addition, those with a production approach had higher MTEs than did those using the intermediation approach, while studies of a large number of MFIs had lower scores than did those involving a small sample size. Moreover, research estimating social efficiency generated lower MTEs compared to those estimating financial efficiency. Studies using data from African MFIs obtained lower MTEs than did those on MFIs in Latin America and MENA, which confirms the poor performance of African microfinance.