Over the past few decades, researchers and analysts have been concerned to solve Handwriting recognition problems. The handwritten text requires different applications to recognize its cursive nature. To create an efficient OCR system, it is necessary to pre-process noisy documents, segment the words and characters, and then recognize the written text by identifying it. This research work aims at solving the Recognition problem and explaining how to process the answer script by using an efficient approach. The proposed approach is detailed step by step. the main goal is to choose the right written handwritten answers and to recognize them through the meticulously built tool and by using ML algorithms. Thus built Algol demonstrates how to develop systematic OCR tools using pre-processing, segmentation, and classifiers. The achieved accuracy is 90\% for handwritten Kannada answers.