Mechanical thrombectomy for the treatment of ischemic stroke shows high rates of recanalization; however, some patients still have poor clinical outcome. The canine large vessel occlusion model has been developed to better understand new treatments. This model has a drawback of inconsistent rates of stroke growth. Here, MRI perfusion based time-to-peak maps were used to predict the rate of infarct growth as validated by ADC-derived maps. Classification of canines into either fast or slow evolvers was reliably shown with this method of analysis, allowing for a better understanding of new therapeutics and potentially for better patient selection for thrombectomy.