Development program has been implemented by government has given great attention to eraditen poverty in order to improve social welfare. Poverty alleviation programs require accurate data and reaching up to the smallest areas. Poverty indicators are obtained from the National Socio-Economic Survey (SUSENAS) held by BPS. SUSENAS is designed to get the indicator to estimated until regency/city level, so to get the estimate until the smaller level has not requirements of the sample adequacy. Small Area Estimation can be used to get poverty indicators by optimizing the available data or without the addition the number of samples.This study discusses the application of Elbers, Lanjouw, and Lanjouw (ELL) methods combined with Counterfactual methods toobtain estimates of poverty indicators at the sub-district and village levels in Yogyakarta and to visualize them with poverty map. The data used are Population Census 2010, SUSENAS (2010 and 2018), PODES (2011 and 2018), as well as other BPS publications.The results showed that the estimation of poverty indicators with the ELL method had a relative error value (RSE) compared to the immediate estimation. By obtaining the indicators of poverty at lower levels of aggregation are expected to increase the credibility of government decision-making in poverty alleviation.