Poverty alleviation is a priority area of intervention for government and non-governmentrnorganizations including Sustainable development goal agenda. Although there is a differencernin the characteristics and dimension of the problem, it can be found in both urban and ruralrnareas. Establishing effective tools for indicators and poverty measurements are alsornimportant for a decision making. In addition to the traditional income poverty indicator,rnmultidimensional poverty measurement became the new way of measuring poverty. This studyrncovered the multidimensional poverty status of urban productive safety net beneficiaries inrnAddis Ketema and Kolfe Keraniyo subcities. The study employed cross-sectional method ofrnresearch design and Mixed research method of data gathering and analysis methods.rnExplanatory sequential design method was utilised to collect & analysed the data. HouseholdrnSurvey, Key informant interview and observation were conducted to collect the relevantrnprimary data and secondary data from the relevant organizations & respondents. A total ofrn270 respondents were randomly selected from the six woredas in the study area. Descriptivernmethods and binary logistic regression method was conducted to analyse the data. Alkire andrnfoster method of Multidimensional poverty measurement method were deployed to assess thernseverity and deprivation status of the respondents. Hence, the severity level of poverty isrnaround 25% and observed that the existence of high number of vulnerable households. And itrnalso confirmed the result of OPHI on the existence of high number of vulnerabilitiesrncompared with other regions of the country. The MPI of the addis ketema and kolfe keraniyornfound 14% and 12.7% respectively. On the other hand, although the program contributed onrnthe improvement of income poverty status households, its impact on education, health andrnliving standard of the beneficiaries were insignificant. On the deprivation status of thernhouseholds education (36.4%) and Health (25.3%) were major contributors forrnmultidimensional poverty of households. Economic factors such as unemployment and incomernvariability including inflation were major determinant factors besides to multidimensionalrnindicators. Therefore, from regression result it was noted that, household size, unemployedrnsize, health status, housing ownership status, and person per room of the households werernsignificant positive determinant and contributor while educational status is negativerndeterminant for poverty status of the households respectively. The study recommends revisingrnscale of program support of households which considers the economic context of the countryrnand promoting similar poverty alleviation programs which works on human capital, health,rnimprovement of living standard of householdâ€™s & job creation activities.