This document discusses a study focused on developing a machine learning model to detect extraneous vibrations during the 3D printing process. It highlights the impact of these vibrations on print quality and introduces a system using an Inertial Measurement Unit (IMU) to measure vibrations. Various machine learning models were evaluated for their ability to distinguish between normal printing vibrations and extraneous vibrations, with the Light Gradient Boosting Machine model showing the best performance. The study emphasizes the importance of early detection of defects to save time and cost, contributing to advances in additive manufacturing technologies.