The National Statistical Coordination Board (NSCB) has recently released in cooperation of the World Bank, the local poverty estimates using the Small Area Estimation (SAE) methodology. These estimates were prepared in response to the increasing demand from the policy makers and planners for a more disaggregated set of poverty statistics. Likewise, thru its regional divisions, the NSCB is implementing provincial poverty index mapping. The poverty mapping aims to identify the poor areas in a province as measured by selected socioeconomic indicators presented on maps. The indicators used by NSCB in constructing the maps were based on the Minimum Basic Needs (MBN) indicators that have been derived thru inter-agency collaboration. The research aims to find the relationship between the poverty index mapping indicators and composite indices with poverty incidences of the SAE. Furthermore, this study attempts to find a way to improve the methodology of the poverty mapping vis-à-vis the SAE. Results of the study indicated that the education indicators and consequently the education composite index have positive linear relationships with the SAE poverty incidences among the four provinces covered by the study. Half of the total 50 poverty indicators from all provinces are negatively correlated with SAE poverty incidences. A weighting model was developed to improve the poverty index mapping methodology and the model performed relatively well in improving the linear relationship of the poverty indices to the poverty incidences.