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Statistical reasoning is a major requirement in the era of big data. Therefore, there is a need to conduct a research about this statistical reasoning. One important study in statistical reasoning is the levels of statistical reasoning. The levels of statistical reasoning are based on the construction of a conceptual framework. This research aimed to describe seven levels of students- statistical reasoning in predicting data. The subjects of this research were 40 students of second semester taken from two different classes. This was conducted in order to fulfill all levels of reasoning. At first, the subjects were given a test, and then 7 students were selected to be interviewed related to the levels of statistical reasoning respectively. Data triangulation was done to maintain the validity and reliability of the data generated. There are seven levels of statistical reasoning in predicting data, namely, the levels of pre-idiosyncratic, idiosyncratic, verbal, transitional 1, procedural, transitional 2, and integrated processes. These seven levels can be used as a consideration in compiling assessment rubrics in statistical material. The assessment should not only focus on students skill in calculating and ability in problem solving but also emphasize on the aspect of reasoning.