Ongole Crossbreed cattle is the largest cattle in Indonesia. Indonesian consume it’s beef in a large amount. Classification effects beef’s quantity and quality. However, the classification process is measuring manually one by one all this time. Moreover the current standard is too high and inappropriate due to the real exist conditions. Seeing the importance of classification, it is necessary to make a system that is able to classify Ongole Crossbreed cattle stocker.This system will measure quantitative requirement parameters from the image. This system will classify using image processing. Implementation of the system is using Matlab software. This system will classify into four classes, namely class I, class II, class III, and external class III. According to the results, it is obtained that the system is able to measure the body lenght, the chest circumference, and the height with accuracy rates are 90,77%, 93,30% and 93,13%. This system is able to classify the class of Ongole Crossbreed cattle stocker with accuracy rate is 86,67%