It is human nature to give prime importance to facial appearances. Often, to look good is to feel good. Also, facial features are unique to every individual on this planet, which means it is a source of vital information. This work proposes a framework named E-Pro for the detection and recognition of faces by taking facial images as inputs. E-Pro has its potential application in various domains, namely attendance, surveillance, crowd monitoring, biometric-based authentication etc. E-Pro is developed here as a mobile application that aims to aid lecturers to mark attendance in a classroom by detecting and recognizing the faces of students from a picture clicked through the app. E-Pro has been developed using Google Firebase Face Recognition APIs, which uses Euler Angles, and Probabilistic Model. E-Pro has been tested on stock images and the experimental results are promising.