Agriculture takes the lion’s share to Ethiopia’s economy, serving as the main source of employment, income, and food security for smallholder farmers. However, the sector remains highly vulnerable to climate change due to its heavy reliance on erratic rainfall. This study aimed to identify the determinants of Climate-Smart Agriculture (CSA) practice adoption and assess its impact on the food security of smallholder farmers. A cross-sectional survey of 260 smallholder farmers was conducted using multistage sampling. The Multivariate Probit Model was employed to identify adoption determinants, while the Endogenous Treatment Effect model was used to estimate CSA’s impact on food security. Findings revealed that farmers were most likely to adopt crop diversification (50.4%), followed by water management (49.9%) and soil and land management (48.3%). The joint adoption probability was 3.02%, while the likelihood of adopting no CSA practices was only 4.5%, indicating strong complementarities among practices. The analysis confirmed both synergies and trade-offs in CSA adoption patterns. The Endogenous Treatment Effect model demonstrated that CSA adoption significantly improved food security, increasing daily calorie intake by 217.59 kcal per capita among adopters compared to non-adopters. The results were robust, supported by strong instrument relevance and model validity. The study concludes that enhancing CSA adoption can significantly improve food security and smallholder livelihoods. Therefore, promoting CSA through field demonstration by development agent works, strengthening cooperatives, irrigation investment, farmer training, and access to affordable credit is recommended to empower farmers, enhance productivity, and support sustainable agricultural development in line with national and global climate resilience goals.

Background: Livelihood diversification is widely recognized as a vital strategy for improving food security among smallholder rural households. However, achieving meaningful diversification remains a challenge due to various socioeconomic and institutional constraints. This study investigates the impact of livelihood diversification on food security in the West Gojjam Zone of Ethiopia. Methods: A cross‐sectional research design was employed using primary data collected from 390 randomly selected smallholder farmers through a multistage sampling technique. Binary logistic regression was used to identify factors influencing livelihood diversification, while Propensity score matching (PSM) was applied to estimate its causal impact on food security. Robust standard errors were reported to address potential heteroscedasticity, and diagnostic tests confirmed no major multicollinearity or model misspecification issues. Key Results: Among the sampled households, 108 engaged in livelihood diversification. Regression results revealed that education (+15.4%) and household size (+5.9%) significantly increased the likelihood of diversification, whereas access to irrigation (−35.7%), livestock ownership (−2.9%), and credit access (−12.08%) negatively affected it. PSM analysis confirmed a positive and statistically significant impact of diversification on food security, increasing daily kilocalorie intake by 118–136 kcal. Conclusion/Policy Implications: The findings suggest that livelihood diversification significantly enhances food security among smallholder farmers. Therefore, policies should promote diversification through expanded irrigation infrastructure, vocational training (TVET and universities), and support for activities such as animal fattening, dairy farming, and beekeeping. Extension services and microfinance institutions should be mobilized to provide technical and financial support focused on diversified farming strategies.

Despite being highly dependent on erratic rainfall and frequently affected by drought and low productivity, agriculture remains the dominant economic activity in Ethiopia. The use of Climate-Smart Agriculture technologies can improve farming productivity, make it more resilient, and help fight climate change by using five Climate-Smart Agriculture practices: growing different crops, raising different animals, using irrigation, planting trees alongside crops, and applying chemical fertilizers in selected areas. Data were collected from 236 households using a multistage sampling technique and gathered through structured questionnaires, key informant interviews, and focus group discussions, the multivariate probit model revealed that key determinants of Climate-Smart Agriculture adoption included the gender of the household head, education level, farm size, income, access to irrigation, availability of credit, extension services, and farming experience. To advance crop and livestock diversification, policymakers should expand irrigation infrastructure, strengthen extension services, and integrate climate-smart advisory programs. Promoting irrigation adoption requires improved access to credit, timely climate information via SMS, farmer training, and targeted awareness campaigns for experienced farmers. There is also clear evidence of complementarity and trade-offs in the adoption of multiple Climate-Smart Agriculture practices in the study area.

The adoption of agricultural technology by smallholder farmers plays a pivotal role in accelerating Ethiopia′s economic transformation, particularly within the agricultural sector. Despite government policy initiatives that actively support agricultural technology, there is still a significant adoption gap among smallholder farmers because of institutional, environmental, and resource limitations. This study is aimed at exploring the factors influencing the adoption of the improved maize variety, BH660, among smallholder farmers in Womberma district, West Gojjam Zone, Amhara Regional State. The research utilized primary cross‐sectional data collected from a total sample of 370 smallholder farmers. A multistage sampling method was employed, with respondents selected using a probability proportional technique. The collected data were analyzed using a binary logit model to identify the most significant determinants of BH660 adoption. With 79.08% of the observations properly classified (80.85% sensitivity and 77.20% specificity), the empirical model showed a strong fit. The results of the regression analysis showed that BH660 adoption was positively and statistically significantly impacted by gender, educational attainment, and access to training, market information, positive behavioral attitudes, and agricultural experience. In particular, calculated marginal effects showed that the likelihood of adopting the hybrid seed was raised by 43.5% and 28.4%, respectively, by having a favorable behavioral attitude and receiving regular market information. Adoption likelihood was also raised by 25.4%, 28.2%, and 25.5% for men, literacy, and training and by 0.8% for every year of farming experience. Based on these results, regional policy actors can take advantage of these important drivers by putting in place functional adult literacy programs, growing Farmer Training Center activities, and adopting gender‐responsive extension frameworks to effectively increase adoption rates and foster sustainable agricultural development.

To enhance food security and reduce poverty, Ethiopian agriculture needs to shift from subsistence production toward a more commercialized system that supp