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Background: In most of the countries, students have to select a subject/stream in the secondary education phase. Selection of subject/stream is crucial for students because further their career proceeds according to their selection. Mostly subject/stream selection cannot be changed in the further career. Inappropriate selection of subjects due to parental pressure, lack of information etc. can lead to limited success in the selected stream. Guidance for subject/stream selection based on information of successful scholars of their stream and information of students such as interest, family background, previous education and other associated can enhance the success in career. Methods: Data mining and machine learning based methods were developed on the above information. Data from the different institutions and students of two different streams were used for training and testing purposes. Different machine learning algorithms were used and methods with high accuracy (86.72) were developed. Result: Developed methods can be extended and used for different subject/stream selection.