The necessity to reduce subjectivity in EEG analysis, reliably expand its diagnostic scope, and gain a deeper understanding of pathophysiology has driven the development of numerical EEG (qEEG) analysis tools. In clinical practice, a qEEG system should be relatively simple in its mathematical foundation, easy to interpret, directly related to the pathology, friendly, and open. At the Hospital de la Princesa, since 2016, we have developed a MATLAB-based method with these characteristics, which we call Cerebral Research and Analytical EEG (CRANE). This package allows dynamic and static analyses, both for band-based power spectral measurements and for synchronization measures, such as Pearson’s correlation coefficient and coherence. We can analyze specific periods of a recording (e.g., pre-ictal, ictal, and post-ictal), statistically comparing both periods. We can also compare different recordings, from different patients or from the same patient, even those taken years earlier. This is very important for truly comparing the patient’s evolution. Other applications include long-term monitoring in ICUs, cross-correlation analysis of specific channel pairs, and graph-element averaging.