This project shows how we can implement an algorithm for the detection of handwritten expression evaluators to build a system that will evaluate the results of the raw user input or image. As we know, we have to manually calculate handwritten expressions which are tedious and time-consuming. In the traditional method, the user has to use a calculator or calculate the result of the expression themselves. Not only that student from primary levels is learning the mathematical expression using traditional memorizing methods which is not as efficient as the learning done with more exciting and entertaining way. Therefore, the proposed solution is to develop a working prototype of a system that provides result based on the handwritten digits and expressions with its value. The main goal of this project is to use the Convolutional Neural Network (CNN) algorithm to identify the handwritten number. Another part of this system is to give the result automatically based on the recognized digit and expression.