The aim of this research is to analyse the vegetation cover of Varaždin County using machine learning methods. The most commonly machine learning methods used in the analysis of vegetation cover through pattern recognition and in - depth data analysis were singled out. The paper provides an overview of the significant and most important satellite missions for imaging of the Earth 's surface that have enabled the collection and use of high and very high resolution satellite imagery. Sentinel-2 images of Varaždin County area were used in this paper. They were analysed in 4 different time periods between 2015 and 2021, and for the processing of satellite images, their classification and subsequent analyses open source programs SAGA-GIS and QGIS were used. Finally, the analysis of vegetation cover was performed using the vegetation index NDVI, after which the results were presented and a conclusion was reached on changes in vegetation cover in the observed area. The results of the support vector machines show that the vegetation cover in Varaždin County area has decreased by 12.94% within 6 years. A random forest shows similar results with a reduction of 10.55%, while the maximum likelihood classifier shows a reduction of 8.42%. The NDVI results show a 10% reduction in very high vegetation cover. The conclusion of this paper is that larger samples taken for forests, low vegetation and water allowed better classification, while smaller samples of arable land and built-up areas gave worse classification of these classes in the observed area. The best method was the maximum likelihood classifier with the most accurate and precise classification results for all classes, and all the methods proved to be very good for analysing the vegetation cover in the observed area.