Creative types of progress in the domain of Medical data course of action have astounded the globe. Reliably another application is made by learned individuals in the locales of Medical data course of action and is being used to foresee various supportive human administration applications. Data examination, data warehousing, data mining, man-caused prevailing upon AI, and related stages to have made outstanding degrees of progress in predicting. Throughout the latest couple of years, human administrations have become a costly illegal relationship inciting severely masterminded impacts on care quality and increasing expenses of medications. Makers over the globe are going after organizing models to predict disorders, for instance, heart issues, neurological disarranges, liver ailments, and some more. The current unique duplicate is being planned to structure desire models subject to SVM and Naïve Bayes models to foresee the headway of pregnancy in women of different age social events. In continuation, these desire models are a promising strategy for utilizing the propelling digitization of therapeutic administrations that gives palatable extents of clinical informational collection aside in Electronic Health Records (EHRs) and association it to the current day uses of Machine Learning. Pregnancy is normal miracle in woman over the globe. In any case, all around the seeing of pregnancy diverts into a test legitimately from the earliest starting point until the presentation of the child. For a woman who is generally scattered in the common areas, who can't stand to go divisions to screen their pregnancy routinely, a gadget reliant on AI can be of most extraordinary help to a clinical master, he with the usage of the estimate models portrayed in this unique duplicate can screen the pregnancy by the snap of a mouse. In this unique duplicate, the models subject to SVM would be thought about, to appreciate parameters like watching Blood tests to check acquired ailments, blood counts, beat, glucose levels, hormonal assortments, amniotic fluid appraisal, villus evaluation and checking diet necessities in pregnant and lactating woman. The caused models to can, in like manner, be observationally assessed similarly as predicting dismal clinical results.