Nociception is a sensory process provoked by external stimuli that trigger a series of physiological reactions that are experienced as pain. The way it is perceived becomes subjective, as it can vary depending on the emotions and behavior of each person, so analog pain scales have been developed, and new technologies are making an effort to find biomarkers that make these evaluations more quantitative and less subjective. In this research, we propose to detect and classify nociceptive pain caused by applying a transcutaneous laser with 3 different intensities using information from Electroencephalographic (EEG) signals. This study aims to be able to classify between pain and non-pain states of 8 subjects using the biosignals of the database, it also is planned to classify between 3 levels of pain linked in an assumption to the 3 intensities of lasers used as noxious stimuli. The results when classifying pain and non-pain states for each participant are greater than 65% of accuracy.