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In the evolving world, we require more additionally the young era to flourishand evolve into developed land. Most of the population all around the world areunaware of the complications involved in the routine they follow while they arepregnant and how hospital facilities affect maternal health. Maternal Mortalityis the death of a pregnant woman due to intricacies correlated to pregnancy,underlying circumstances exacerbated by the pregnancy or management of thesesituations. It is crucial to consider the Maternal Mortality Rate (MMR) indiverse locations and determine which human routines and hospital facilitiesdiminish the Maternal Mortality Rate (MMR). This research aims to examine anddiscover the countries which are keeping more lavish threats of MMR andcountries alike in MMR encountered. Data is examined and collected for variouscountries, data consists of the earlier years' observation. From theperspective of Machine Learning, Unsupervised Machine Learning is implementedto perform Cluster Analysis. Therefore the pairs of countries with similar MMRas well as the extreme opposite pair concerning the MMR are found.

Estimating Countries with Similar Maternal Mortality Rate using Cluster Analysis and Pairing Countries with Identical MMR