Machine learning Recent works on ensemble [1] methods like Adaptive Boosting have been applied successfully in many problems. Ada-Boost algorithm running on a given weak learner several times on slightly altered data and combining the hypotheses in order to achieve higher accuracy than the weak learner. This paper deals with the design and development of an expert system to advice the farmers in villages through online. An expert system is a computer program, with a set of rules encapsulating knowledge about a particular problem domain. This is a web based application developed using machine learning techniques. In the present paper, Ada-Boost algorithm technique has been considered and applied to generate conclusion based on the given training data provided by human expert. Here a rule based expert system and machine learning systems are integrated to form the proposed Ada-Boost Algorithm Using Naïve Bayesian Classifier on Maize expert Advisory System. The proposed system examines the symptoms provided by the user and process the information based on the training data and determines the diseases effected to the Maize crop. The system shows a global solution for recognizing the diseases in Maize crop cultivation and also suggests the corresponding treatments to the diseases. This expert system is a web based application for online users with java as front end and MYSQL as backend.