Ovarian cancer usually has a relatively poor prognosis. It is disproportionately deadly because it lacks any clear early detection or screening test, meaning most cases are not diagnosed until they have reached advanced stages. However, in some cases, ovarian cancer recurrences are chronically treatable. Ovarian cancer metastasizes early in its development, often before it has been diagnosed. High-grade tumors metastasize more readily than low-grade tumors. Typically, tumor cells begin to metastasize by growing in the peritoneal cavity. More than 60% of women presenting with ovarian cancer have stage-III or stage-IV cancer, when it has already spread beyond the ovaries. Ovarian cancers shed cells into the naturally occurring fluid within the abdominal cavity. These cells can then implant on other abdominal (peritoneal) structures, included the uterus, urinary bladder, bowel, lining of the bowel wall, andomentum, forming new tumor growths before cancer is even suspected. Since a large number of people are affected by this type of cancer, we have chosen to investigate on the insilico studies of this cancer. From the results obtained from this present research project we predict the Highly Expressed genes of Ovarian cancer induction using Codon usage. We found out the various genes involved in Ovarian cancer and predicted the Insilico Gene expression levels and found out the Highly Expressed genes. We also modeled the structural attributes employing Comparative Modeling and Docking.