Assisted reproduction by in-vitro fertilisation plays a pivotal role in the treatment of infertility, the understanding of reproductive biology, and future population dynamics. The success of assisted reproductive technologies (ART) is critically dependent on optimizing protocols for controlled ovarian stimulation which aim at providing an adequate number of good quality oocytes for in-vitro laboratory procedures. Interindividual variation in response to follicle-stimulating hormone (FSH) is a widespread problem with clinical and economical implications. A group of patients (9%-24%) tend to respond poorly to controlled ovarian stimulation (COS) whereas other patients tend to overrespond (2.5%) and thus run at risk of developing ovarian hyperstimulation syndrome, a potentially life-threatening disease. Polymorphisms of gonadotropin receptors seem to have an influence on the outcome of controlled ovarian hyperstimulation treatment, e.g. contributing to the variation in ovarian response to exogenous FSH between individuals. Other predictive factors include demographic (age), sonographic (follicular count in the ovaries, ovarian volume), endocrine (serum gonadotropin levels and Anti-Muellerian Hormone) and life-style factors (smoking, obesity). Such factors are routinely obtained prior to a treatment cycle, and are used to determine the optimal FSH starting dose or the best treatment regimen. The identification of gonadotropin receptor polymorphisms and variants in secreted gonadotropins prior to an ovarian stimulation treatment should allow the clinicians to tailor the starting dose of rFSH, especially for patients undergoing their first treatment cycle, as such ovarian response prediction will prevent cycle cancellations due to too low or too high ovarian response and reduce the risk of OHSS. The aim of the present study is to identify the prevalence of FSH and LH receptor polymorphisms and hormonal variants of LH and to study the variation attributable to these genetics factors when controlling for already established predictors of ovarian response to exogenous FSH in a multi-variate analysis.