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This paper is dedicated to modeling extreme TEC (Total Electron Content) values at the territory of Serbia. For the extreme TEC values, we consider the maximum values from the peak of the 11-year cycle of solar activity in the years 2013, 2014 and 2015 for the days of the winter and summer solstice and autumnal and vernal equinox. The average TEC values between 10 and 12 UT (Universal Time) were treated. As the basic data for all processing, we used GNSS (Global Navigation Satellite System) observation obtained by three permanent stations located in the territory of Serbia. Those data, we accept as actual, i.e. as a "true TEC values". The main objectives of this research were to examine the possibility to use two machine learning techniques: neural networks and support vector machine. In order to emphasize the quality of applied techniques, all results are adequately compared to the TEC values obtained by using International Reference Ionosphere global model. In addition, we separately analyzed the quality of techniques throughout temporal and spatial-temporal approach.

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