This document describes different E-Senses systems, such as Electronic Nose, Electronic Tongue, and Electronic Eyes, which were used to build several machine learning models and determine their performance to classify a variety of Colombian herbal tea brands such as Albahaca, Frutos Verdes, Jaibel, Toronjil, and Toute. To make this, a set of Colombian herbal teas samples were previously acquired and processed through multivariate data analysis techniques (Principal Component Analysis, Linear Discriminant Analysis) in order to feed the Support Vector Machine, K-nearest neighbors, Decision Trees, Naive Bayes, and Random Forests algorithms. The data acquired from all the devices were merged to enhance the classification success rate. The results of the E-Senses were validated using the HS-SPME-GC-MS analysis, where the best machine learning models from the different classification methods reached a 100 % success rate in classifying the samples