Wheat, a vital staple crop in Ethiopia, plays a key role in ensuring food security due to its widespread consumption, adaptability to diverse agro-ecological zones, and significant contribution to food availability. Recent national efforts to increase wheat production have included expanding the use of agricultural machinery; however, the effects of mechanization, especially among smallholder farmers, on wheat yields and efficiency remain insufficiently studied. To address this gap, this study applies a Stochastic Frontier Model (SFM) with selection correction alongside a Multinomial Endogenous Switching Regression (MESR) model to estimate technical efficiency and evaluate the impact of mechanization. Using data from 409 wheat farmers in the Arsi Zone, Oromia Region, results reveal substantial variation in technical efficiency across mechanization groups, with farmers using both tractors and combine harvesters achieving the highest efficiency scores (.95). Additionally, the Stochastic Production Frontier analysis shows that fertilizer inputs (DAP and urea) positively influence wheat output regardless of mechanization status. The MESR findings indicate that adopting machinery, whether tractors, combine harvesters, or both, significantly improves technical efficiency and yields. These outcomes highlight the need to improve farmers’ access to mechanization services, strengthen extension support, and enhance information dissemination to increase adoption rates and boost wheat production among smallholder farmers in Ethiopia.