The star formation rate (SFR)-stellar mass (M∗) relation of galaxies has long been a subject of research interest in astronomy. Why do galaxies with similar stellar masses have different star formation rates? What are the underlying mechanisms for such a difference? To address these questions, in this study, I utilize the large spectroscopic data from the Sloan Digital Sky Survey (SDSS) and the deep imaging dataset obtained by the Hyper Suprime-Cam (HSC) Survey to investigate the impact of galaxy mergers on the star-formation rate. I first use the HSC images to find a subset of galaxies undergoing the merging process and apply a machine learning algorithm for identifying all the merging galaxies in the SDSS dataset with HSC observations. I then analyze the effects of different stages of mergers on the SFR-stellar mass relation and compare it with the relation of isolated galaxies. Finally, the results show that on average, galaxy mergers have approximately 2 times higher star formation rates than isolated galaxies with similar stellar masses. This result demonstrates that the merging of galaxies is one of the key mechanisms that affect star formation rate (SFR)-stellar mass (M∗) relation of galaxies.