Data mining is one of the techniques to extract useful information from a huge data and support to make decision in various aspects. In academic institutions like universities and colleges the students placement in to different departments is one of the activity that data mining can be applied to predict the departments which the students will be placed based on the order of their preference. Educational Data Mining is concerned with developing new methods to discover knowledge from educational database and can used for decision making in educational system. In this study, we collected the student's data that have different information about their entrance exam result and then apply different classification algorithm using Data Mining tools (WEKA) for analysis of student's placement into departments. The study used three algorithms J48, Naive Bayes and Random Forest to build a prediction model for placement of students. The analysis result shows that Random Forest algorithms has performed well and can be used as a best predicting model algorithm than the other two algorithms. Finally the output shows that most of the students were placed based on their first choice and only some of them were placed without their first choice.