Composting process depends on microbiological decomposition of organic matter in oxygenic conditions proceeded by the thermopile microorganisms and moulds. During the process there is a lot of heat energy emission which can be used for different aims. There is no information about neural network used for modelling of composting processes in the world publications. The objective of presented work was to model the composting process of solid natural fertilizers using the artificial neural networks. I focused mainly on thermal analysis of this process. Qualification of heat emission as a result of exothermic reactions during composting process was the focus of attention. The second stage was complex analysis as well as creating, testing and verification of series of neural networks topology. The analytical software package Statistica v. 7.1: 'Neural Networks' was used. Low ratio of standard deviations and correlation coefficient close to one, provide the most important information for the good assessment of the neural network.