Laportea decumana (Roxb.) Wedd. is a medicinal plant from Papua containing diverse secondary metabolites with reported pharmacological activities. This study aimed to explore potential antimalarial metabolites from L. decumana using an in silico-guided isolation approach. Previously identified metabolites were computationally screened against an antiplasmodial target based on predicted binding energies. The plant material was sequentially extracted using n-hexane, ethyl acetate, and ethanol, followed by vacuum liquid chromatography, TLC-guided fraction pooling, subfractionation, and compound isolation. The ethyl acetate extract showed the highest yield (9.3%) and contained prioritized metabolites with favorable predicted binding energies, including robustaflavone (−10.77 kcal/mol), neogogenin acetate (−8.57 kcal/mol), apigenol (−8.32 kcal/mol), kaempferol (−7.97 kcal/mol), and nobiletin (−7.84 kcal/mol). Vacuum liquid chromatography produced 16 fractions grouped into five pooled fractions based on TLC profiles. Further purification yielded two isolates, β-carotene and xanthophyll. These findings demonstrate that computational prioritization can guide chromatographic isolation of potential antimalarial metabolites from L. decumana. Structural confirmation and direct antiplasmodial testing are required to validate their biological activity.