Machine Learning (ML) has shown its capacity for solving problems where prediction is a key factor, and the fact led us to start to explore ML in Data-prefetching, where prediction is also a key factor. Among various ML algorithms, Perceptron Learning caught our attention because of its simplicity that could make it fit well for microarchitecture design. Therefore, we propose Perceptron based Data-prefetching in this paper, contributing to the state of the art by presenting the followings: a novel memory address prediction algorithm based on Perceptron Learning; the hardware implementation thereof; and the evaluation results with an industry-standardized benchmark suite.