The accuracy of real-time PCR (RT-PCR) experiment is strongly dependent on the mathematical models of data analysis, on which the quantitative methods are based. In this review, we discuss the key steps of analysing data from real-time PCR experiments. These are the treshold cycle determination, estimation of real-time PCR amplification efficiency and amplicon quantification. The fit point method and the second derivative method are commonly used to determine a treshold cycle value, which is a cycle number in the early exponential phase of PCR that is used to calculate the initial amount of template DNA. The amplification efficiency calculation is usually based on the data collected from a standard curve. However, in the alternative methods, the amplification efficiency of an individual reaction is calculated from the kinetics of the reaction. Quantification of amplicon levels can be either absolute or relative. In absolute quantification method, the initial concentration of target template in unknowns, based on their cycle treshold values, and the construction of an absolute standard curve for each individual amplicon is required. Relative quantification can be done by the use of the relative standard curve method or the comparative method. In the first one, the initial amount of unknown samples is calculated from the standard curve of specific gene and normalized to the input amount of a reference gene which is also calculated from the standard curve. The comparative method is a mathematical model that is based on the differences in the normalized amplicon levels between the unknowns and control sample. There are also models that combine gene quantification and normalization into a single calculation.