Eradicating poverty in all its forms is one of global society's sustainable development goals. This requires creative and rigorous efforts to measure and reduce multidimensional poverty in a way that ensures no one is left behind. Despite a couple of efforts made to measure multidimensional aspects of welfare at the national level, limited studies have been done in rural parts of the country, where most poverty researches focused in unidimensional poverty. Hence, this study quantified the extent and examined the determinants of rural household multidimensional poverty status using the Alkire-Foster method and the ordered logistic regression model, respectively. Crosssectional data set was collected from 397 randomly selected households using structured questionnaire. Living standards indicators contribute the most to multidimensional poverty, while empowerment contributes the least. The study revealed that multidimensional poverty headcount, intensity, and the index were found to be 80.35 percent, 55.97 percent, and 44.8 percent, respectively. Among the sampled households, 2.2 percent of households were non-poor, 17.8 percent were vulnerable, 52.6 percent were moderately poor, and 27.4 percent were severely poor. According to the ordered logit model, the probability of a household being in multidimensional poverty was determined negatively by sex(male), expenditure, family size, land size, and employment level, while age and distance to the nearest health center are positively influencing it. Hence, promoting family planning, diversifying income sources and viable labor-intensive rural employment opportunities, provision of improved energy sources, electricity, clean water, and a road network would reduce a multifaceted rural poverty.
 Keywords: Deprivation Score; Konso; Multidimensional Poverty Index; Ordered Logit Model