Education is one of the necessities of an individual’s life, as it enhances the self-morality and nobility that leads one towards the challenging pathways of the competitive world. In the agricultural based country, education is scarce among the children of the farmers as they suffer from poverty. After affecting with COVID-19, study dropout rate of farmers’ children is increased. We collected raw data from rural areas of different countries, and pre-processed this data before applying the machine learning algorithm to improve the performance. We used advanced machine learning models to predict whether farmer’s children will run or drop out of their education. Based on the outcomes it was viewed that, machine learning strategies substantiate to be suitable in this area. This research proposes preventive steps for dropping out of the farmers' children. It also shows that, the Random Forest being the highest reliable model for foreseeing dropout rate and education level.