Docetaxel has come into wide use recently for the treatment of breast cancer in neoadjuvant, adjuvant and metastatic settings. Docetaxel binds to beta-tubulin and causes kinetic abnormalities in the dynamics of microtubules by increasing their polymerization and inhibiting their depolymerization, resulting in elevated levels of microtubule formation. During metaphase, defective spindle formation induced by docetaxel activates the mitotic checkpoint and leads to cell cycle arrest, culminating in apoptosis. However, docetaxel is not effective for all breast cancers. For example, in metastatic settings, the response rate to docetaxel reportedly ranges from 30 to 50%. It is therefore very important to develop a diagnostic method with high accuracy for the prediction of sensitivity to docetaxel in order to avoid unnecessary treatment. Currently it is impossible to identify, before the initiation of therapy, the patients for whom docetaxel will be effective. Various biological parameters have been studied clinically for their ability to predict response to docetaxel, such as parameters related to: (1) efflux (p-glycoprotein) and metabolism (CYP3A4); (2) beta-tubulin (somatic mutation of beta-tubulin and changes in beta-tubulin isotypes levels); (3) cell cycle (HER2, BRCA1 and Aurora-A); and (4) apoptosis (p53, BCL2 and thioredoxin). More recently, gene expression profiling techniques have been used for the development of a prediction model for response to docetaxel. In the present paper, clinical studies that have been conducted recently to identify predictive factors for response to docetaxel are reviewed together with a presentation of our recent work in this field.