The main objective is using fuzzy classifiers to provide accuracy in the handling of information, which will help to be more accurate when classifying the blood pressure level of a patient. Classifiers are based on the parameters provided by the guidelines, and make the comparison given by the European and the American guide and observe the behavior that each of them can take at the time of making a diagnosis. Based on this study we want to identify the way in which a patient is diagnosed using two different guidelines of blood pressure levels, the first is the European guidelines and the second it is the American guides, the latter mentioned was recently updated and it is important to see the impact that each of them can have on society. Currently there is a database with 200 patients, each patient has an average 45 measurements, these 24-hour screenings have been obtained in collaboration with a cardiologist, and this information is then processed with neural networks to obtain the tendency, which enters in fuzzy classifier, which gives us the blood pressure level depending on the base guideline. The following result was obtained based on the parameters and levels given by each of the guidelines and using fuzzy classifiers respectively for each, which have a correct classification accuracy rate of 100% for the 30 patients processed and classified. For the European guidelines the classification of patients with hypertension is 43.3% with a standard deviation of 2.71 and using the new American guidelines is 56.6%with a standard deviation of 2.71 using the same patients. The performed study reports a higher rate of hypertensive people, which based on European guidelines are within normal to high normal ranges, but based on the new American guidelines it was observed that some patients directly enter the stage 1 or stage 2 hypertensive classes, which generates an impact on their daily life, in which they need to change their lifestyle to avoid a cardiovascular event.