From the middle of the 20th century, producers and genetics experts have intensified the work to improve dairy production. Advances have appeared, however, these results had not been followed by the improvement of cows’ hooves. The intensification of herds’ needs have been carried through housing modifications aiming to adjust them as well as to have them become more productive, leading to a larger concentration of animals, resulting in a bigger volume of dejects, higher humidity, less hygiene, and difficulties of handling. This scenario results in the sprouting of hoof pathologies. This research considered the development of a computational system for preventive diagnosis of confined dairy cattle hoof pathologies in freestall housing, for estimating the presence of laminitis. Clinical diagnosis of the laminitis is only possible by observing faulty locomotion; however, when the symptoms are apparent, the pathology is already in an advanced stage. A correlation with the nutritional factors of feed intake, the presence of abrasive pavements, climatic changes, and handling conditions had allowed the conversion of these data into linguistic terms, and the application of Fuzzy Logic inference algorithms based on a rule database to be used as the decision support process. The results showed that the expert system generates information of possible increases or decreases in laminitis development and also supplies recommendations for producers’ actions by making modifications in parameters regarding environmental conditions, feeding and handling management. The generated technology contributes for the reduction of the economic losses and leads to improvement in dairy cattle welfare.