We studied the dependence of peroxidase (POD) activity on pH in crude extract of Picea omorika (Panc.) Purkinye needles and in its acidic and basic fractions, obtained by ion exchange chromatography. Nonlinear regression was applied on the activity data with pH as the explaining variable, using the Levenberg-Marquardt algorithm. Studying crude extract at three different temperatures, the shape of the simulated activity/pH dependences indicated an existence of two components, which was confirmed by mathematical modeling. The kinetic parameters Act0, KEH and KEOH of both components are presented. The curves and pH optima shifted under increasing temperatures towards lower pH values, which was verified after decomposition. Nonlinear regression detected the presence of two components for both fractions, and there is no considerable difference between their pH optima. Our results show for the first time that the sum of components, each described by the mathematical model employed, can be used to explain the complex pH-related POD activity in the extract with two or more enzyme forms simultaneously active.