Ovarian cancer has proved to be one of the most difficult cancers to treat. It is often diagnosed in the late stages. When it is detected early, the 5-year survival rate is 93%. However, it is only detected early 15% of the time. For this reason, there is an emphasis on finding better tumor markers that can identify cancerous cells early. Ovarian cancers come from 3 different cell types. There are a variety of cancer subtypes from each type of cell. A onesize fits all treatment method isn’t feasible with so much variation. Models of ovarian cancer help understand the pathway of cancer development, find tumor markers for early detection, improve imagining techniques, and test drug therapies. Current models include transgenic mice, xenograft mice, chick chorioallantoic membrane, the laying hen, and 3-D human tissue cultures. Unfortunately, there are plenty of flaws with these models that researchers are trying to overcome. Determining which model is the best representation of human ovarian cancer is crucial for making progress in treating ovarian cancer. In this review I will provide an overview of current models for ovarian cancer. I will be looking at current research done with these models to explore their benefits and disadvantages.