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Child under nutrition is one among the world’s ten most important public health problems. Its effect could be either immediate through increased child morbidity and mortality or later in adult life by affecting health and labor market outcomes. Improving the national nutritional status is a priority area that might affect the focus of nutrition policy of countries. The national demographic and health surveys are the main source of official statistics in developing countries, and generate a range of invaluable data at the administrative level one and national levels. However, there is a rapidly growing demand to produce reliable estimates at the micro administrative level due to small sample sizes. Though there is one study at wereda level in Ethiopia, it has limitations. Therefore, we employed spatial small area estimation techniques to estimate the prevalence of malnutrition at zonal levels among under five children in Ethiopia overcoming the aforementioned limitations. The small area estimation concept was sought by linking the most recent possible survey data and census data in Ethiopia. In order to protect against possible model misspecification as well as possible over shrinkage, the model-based hierarchical Bayesian estimates were bench marked. The result shows that there is spatial variation in stunting, wasting, and being underweight across the zone level, showing that different locations faced different challenges and to different extents of undernutrition. Therefore, public health interventions that reduce undernutrition in zones with a high prevalence of undernutrition are crucial, and the Ethiopian Federal Ministry of Health (FMOH) should design tailored nutritional intervention for children under five who are living in zones with a high prevalence of undernutrition.