Emails are the most common mode of communication for events, assignments, and other notices among DWIT members. The bunch of emails are send to inboxes each day concerning various events, assignments or informational notices. Unfortunately, with so many emails going around, not all of the emails sent out to the inbox can be read or even organized into useful categories that could help disseminate information better. The goal of DWIT Email Classifier is to address this problem, and the approach used is to build a training model using Logistic Regression Classification Model which automatically syncs with the user Gmail inbox and classifies the new, unseen emails into one of the four categories; Club emails, Class emails, Administration emails and Miscellaneous. The 4,000 existing emails were used as the training set in this system.