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Cervical cancer is a cancer caused by an infection derived from the Human Papillomavirus (HPV) that proliferates in the cervical mucosa. Cervical cancer ranks among the two highest incidences experienced by women, with 23.4% and an average death rate of 13.9%. Vascular endothelial growth factor (VEGF) is an important protein that plays a role in the pathology of angiogenesis in tumor growth and metastasis. Various efforts have been made to minimize mortality from cervical cancer, but they have caused side effects. Indonesia is rich in a diversity of flora that has the potential to be used as a natural medicine, for example, soursop leaves (Annona muricata). The study aimed to predict the compound extract of soursop leaves as a candidate drug for cervical cancer based on a silico approach. The prediction of phytochemical properties is made based on the five laws of Lipinski as seen from the values of absorption, distribution, and metabolism with Swiss ADME. The in-silico method was conducted with the assistance of computer devices, databases, and software like Autodock, PyRx, PyMol, and Discovery Studio. The target proteins used are VEGFR1 (PDB: 3HNG) and VEGFR-2 (PDB: 3VHE). The results showed that kaempferol, sativene, and thiazole-2,4(3H,5H)-dione, 5-benzylideno-3-[(ethylphenylamino)methyl] meet the five laws of Lipinski. The compound kaempferol has the lowest binding affinity, with a value of -8.5 kcal/mol on VEGFR-1 and -10.2 kcal/mol on VEGFR-2. On the other side, sunitib interactions with VEGFR-1 were -10.0 kcal/mol and -9.4 kcal/mol, respectively. Based on the results, can be concluded that kaempferol has a high potential to be a drug candidate for cervical cancer.