Infertility affects about 10% of couples in the United States, and the cause of infertility in up to 30% of affected couples remains unexplained. In Vitro Fertilization (IVF) is the most commonly used Assisted Reproductive Technique to address the issue of infertility in couples; however, the low IVF success rates (30-40% for women aged 34 and younger, with decreased success rates for older women) reveals a need for methods to accurately predict IVF success. Current methods for predicting IVF success use pre-implantation genetic diagnosis or morphological assessment of oocytes. However, pre-implantation genetic diagnosis requires embryo biopsy and does not improve live-birth success rate. In addition, morphological assessment is subjective and unquantitative, and often fails to predict IVF success. Therefore, the development of new methods to predict oocyte competence that are non-invasive, quantitative, and accurate would represent a great advance in the field.