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It is a very important the classification of the Cubans petroleum, and stiller, the determination of its destination, to make more efficient its use. The objetive of this paper is to carry out a procedure to get a classification of the Cuban petroleum. For this it was analyzed the nature of the national data of the raw ones and their attributes, which consisted initially of 30 attributes with 54 samples of petroleum and it was determined to process them as attributes divided by intervals. The recognition patterns tools were applied to classify the Cuban petroleum in five established groups: Slight, Medium, Semi-heavy, Heavy and Extra-heavy. The most representative attributes were selected starting from the Informative Weight. Five cases were recognized that were in contradiction with their defined locations initially in the Learning Matrix, these eliminations were justified. The strict similarity was used as proximity measure among the cases. The magnitude of the Learning Matrix was of 22 attributes and 49 cases. Finally, an automatic program was designed for the classification of the raw ones and 98.0% of effectiveness was obtained in the classification of the Control Matrix of 49 samples of Cuban petroleum. [ABSTRACT FROM AUTHOR]