Research of the color features for strawberry leaves sorting and chlorophyll assessment is presented in the paper. The paper presents the possibilities of identifying informative color features using image processing for modeling and predicting chlorophyll in strawberry leaves. The second aim of our research is to classify strawberry leaves into two varieties using image processing and classification procedures. Images of strawberry leaves are obtained using document-camera. Statistical analysis is used for assess the relation between 12 color features from 4 color spaces (RGB, HSV, Lab, and xyz) and chlorophyll content. Seven color components are informative for development of mathematical models for chlorophyll prediction in leaves. Three classifiers decision tree, SVM, and weighted KNN are used for classification the leaves into two strawberry varieties Alba and Asia. Тhe highest аccuracy is achieved with classifier SVM with color combination components RG and RGB.