Cognitive Radio Networks (CRNs) offer a promising capability of alleviating the problem of spectrum insufficiency. In CRNs, the licensed spectrum channels are either exclusively reserved for licensed users or temporarily used by unlicensed users. The requirement for unlicensed users is to not harmfully impair the licensed users transmissions. Because of this, the unlicensed users must solve the task to decide which available channels should be selected. The selection process is often referred to as spectrum decision, with the aim to optimize the transmission performance of unlicensed users. A support system for CRNs is introduced, which is called Spectrum Decision Support System (SDSS). SDSS provides an intelligent spectrum decision strategy that integrates different decision making algorithms and takes into account various channel characterization parameters. The objective is to develop a scientific framework for decision making in CRNs, which involve theoretical analysis, simulation evaluation and practical implementation. Three important components of SDSS are discussed: 1) setting up an overlay decision maker, 2) prediction based spectrum decision strategy and 3) queuing modeling of CRNs. The reported results indicate the feasibility of the suggested algorithms.