Breast cancer represents a heterogeneous group of tumors with varied morphologic and biological features, behavior, and response to therapy. The present routine clinical management of breast cancer relies on the availability of robust prognostic and predictive factors to support decision making. Breast cancer patients are stratified into risk groups based on a combination of classical time-dependent prognostic variables (staging) and biological prognostic and predictive variables. Staging variables include tumor size, lymph node stage, and extent of tumor spread. Classical biological variables include morphologic variables such as tumor grade and molecular markers such as hormone receptor and human epidermal growth factor receptor 2 status. Although individual molecular markers were introduced in the field of breast cancer management many years ago, the concept of molecular classification was raised after the introduction of global gene expression profiling and the identification of multigene classifiers. Although there is no doubt that gene expression profiling technology has revolutionized the field of breast cancer research and have been widely expected to improve breast cancer prognostication, the unprecedented speed of progress and publicity associated with the introduction of these commercially-based multigene classifiers should not lead us to expect this technology to replace the classical classification systems. These multigene classifiers have the potential to complement traditional methods through provision of additional biological prognostic and predictive information in presently indeterminate risk groups. Here we present updated information on the present clinical value of classical clinicopathologic factors, molecular taxonomy, and multigene classifiers in routine patients management and provide some critical views and practical expectations.