Improving household income source is a prerequisite for sustainable development and pro-poor growth in developing nations. Achieving this objective requires poorest inclusive sound policy and holistic approach were important. Poor base issues like food security, any income generative activity, improved productions and capacity building to also be integrated into any development programs. Therefore, this study was conducted to analyze the impact of programs on household income in Lasta District. Data were generated from 262 households using a systematic sampling technique from sample kebeles. The study used both primary and secondary data. Descriptive statistics, inferential statistics, and econometric models were used to analyze the collected data. The collected qualitative data from key informants and FGD were interpreted by using narrative tools. PSM model were employed to analyze determinants of a beneficiary and program's impact on household annual income. Household size, land size, and having off-income were statistically significant at 1% probability, whereas the age of the households was significant at 5%, while saving ability, credit access, market distance, households educations status, sex of households and marital status were less significant. The propensity score estimation for matching has resulted in 127 non-beneficiaries households matching with 114 beneficiary households. 241 households were identified and considered as impact estimation process after discarding 21 households. A balance test was applied to check the balance of relevant variables in both groups after matching. The test result indicates that after matching no significant variation between the groups. Finally, the kernel matching estimator was selected as a best matching algorithm to evaluate the impact. Therefore, the model result shows that the households’ income scores of beneficiaries and non-beneficiaries were 30879.63 ETB and 19889.24 ETB. The study concludes that there is a positive mean difference between the two groups on annual income 10989.82 ETB. Based on the finding, the program should primarily focus on addressing constraints (i.e. Lack of capital and weak market chain).