Abstract: Machine Learning is widely used to program and develop computer systems that are able to perform without explicit instructions, by using existing algorithms to analyse and find patterns in data. Machine learning uses existing algorithms and makes a prediction. If the predictions made are ambiguous and not so clear we use meta learning for the predictions. Meta-learning learns and makes a prediction of predictions made by machine learning algorithms. Simply, Meta-Learning makes the best use of predictions made by machine learning algorithms to make an accurate prediction. This research makes use of algorithm like adaboost to boost the performance of existing machine learning algorithms. Simply put it is used to achieve higher accuracy rate for the existing machine learning algorithms or models. Adaboost algorithm mostly uses a one split decision trees for ensembling. Abstract Boosting is an approach to machine learning based on the thought of making a profoundly precise forecast run the show by combining numerous generally powerless and wrong rules. In this model we predict the illness of five individuals of middle aged using adaboost model.