Current work is describing approach for interpretable if-then rules extraction from piecewise linear classifier. Such classifier can be built based on many black-box classifiers like RBF Neural Network, Multi Surface Method tree or can be created from scratch [1, 2]. Approach used to extract knowledge in the form of if-then rules from piecewise-linear classifier is extension of method proposed by [3] used to extract knowledge from linear SVM. We describe optimization problem, recursive algorithm used to extract if-then rules and its complexity. As well we present some experimental results highlighting proposed approach performance.