Studies of ovarian development in female mammals have shown a relationship between the day in the estrous cycle and the size of the main structures and physiological status of the ovary. This paper presents an algorithm for the automatic classification of bovine ovaries into temporal categories using information extracted from ultrasound images. The temporal classes corresponded roughly to the metestrus, diestrus, and proestrus phases of the bovine reproductive cycle. Features based on the sizes of ovarian structures formed the patterns on which the classification was performed. A Na??ve Bayes classifier was able to correctly classify the stage of the estrous cycle for 86.36% of the test patterns. A decision tree classified 100% of the test patterns correctly. The decision tree inference algorithm used to build the classifier constructed a tree that used only two of the five available features indicating that they form a sufficiently rich set of features for robust classification.