Dyslipidemia is a condition of lipid metabolism characterized by an imbalance of total cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), and triglyceride levels in the blood. This biosynthesis process can occur through a mechanism modulated by β-Hydroxy β-methylglutaryl-CoA (HMG-CoA) reductase. The most commonly used drug that works by inhibiting this enzyme is simvastatin. However, there are still significant side effects. In this work, in silico studies were performed on compounds from black cumin (Nigella sativa L.), namely alpha-pinene, p-cymene, nigellimine N-oxide, nigellidine, carvacrol, alpha-hederin, dithymoquinone, thymohydroquinone, thymoquinone, thymol, and nigellicine to predict their activity against HMG-CoA reductase as drug candidates in the treatment of dyslipidemia. The experiments were carried out using computational approaches, such as Lipinski's Rule of Five and ADMET prediction, pharmacophore modeling, and molecular docking simulation. Based on the molecular docking results, there are three compounds that exhibit strong interactions with amino acid residues on HMG-CoA reductase, which have the lowest binding energy values and inhibition constants: nigellicine (-6.84 kcal/mol, 9.71 μM), nigellidine (-6.44 kcal/mol, 19.16 μM), and nigellimine N-oxide (-6.14 kcal/mol, 31.34 μM). These three compounds have potential and can be modified to become candidates for antidyslipidemic drugs with a competitive inhibitor mechanism.