Currently, artificial intelligence (AI) technology is ubiquitous across various domains, serving as a highly effective tool to assist humans. The pharmaceutical sector, in general, and drug manufacturing and development, in particular, are capitalizing on this opportunity by employing in silico models to discover new drugs. This study is one such endeavor, utilizing an in silico model to predict the inhibitory potential against HepG2 cancer cells of Triterpenoid derivatives from the Paramignya Trimera. Quantitative Structure-Activity Relationship (QSAR) models were employed to forecast IC50 values for newly designed compounds. Following the screening for drug-like properties, molecular docking was performed on the Bcl-2 receptor of HepG2 liver cancer cells. Among 196 newly designed compounds, after successive screening steps, TPN61 emerged as a potential inhibitory compound against Hep-G2 cancer cells derived from Triterpenoids of the Paramignya Trimera. Citation this article (T. U. Tran & Nguyen, 2024) Tran, T. U., & Nguyen, M. Q. (2024). THE DESIGN AND SCREENING OF COMPOUNDS INHIBITING THE PROLIFERATION OF HEPATIC CANCER CELLS (HEP-G2) WERE CONDUCTED UTILIZING SEVERAL TRITERPENOID DERIVATIVES DERIVED FROM THE PARAMIGNYA TRIMERA PLANT. Hoa Sen University Journal of Science , 03, 44–55. https://vjol.info.vn/index.php/dhs/article/view/94037