Duchenne muscular dystrophy (DMD) is a fatal X-linked muscle disorder caused by mutations in the dystrophin gene with a consequence of progressive degeneration of skeletal and cardiac muscle. Golden retriever muscular dystrophy (GRMD) is a spontaneous X-linked canine model of DMD with similar effects. Due to high soft-tissue contrast images, MRI is preferred as a non-invasive method to extract information corresponding to biological characteristics. We propose and evaluate non-invasive MRI-based imaging biomarkers to assess the severity of golden retriever muscular dystrophy (GRMD) using 3T and 4.7T MRI data of nine animals. These imaging biomarkers use first order statistics and texture (assessed by wavelets) in quantitative MRI (qMRI). In a leave-one-sample-out cross-validation framework, we use SVM to differentiate between young and old GRMD animals. The preliminary results show good differentiation between young and old animals for different qMRI sequences and based on a different selection of features.