Using machine learning and natural language processing methods, this paper intends to create an automated essay grading system. Essays submitted for the IELTS and TOEFL tests are evaluated using Long Short-Term Memory (LSTM) and Support Vector Machine (SVM) models. The essays are graded on a scale from 1 to 5 based on the system’s analysis of many factors, such as cohesion, syntax, vocabulary, phraseology grammar and conventions. The model learns the associations between language characteristics and evaluation scores by studying a dataset of essays that have already been graded. To evaluate the system’s performance, it is first applied to a new pool of essays. Since the suggested approach does not rely on human subjectivity or prejudice, it has the potential to enhance the efficiency and uniformity of essay grading. As a whole, this work illustrates how machine learning and NLP may be used to create useful tools in the field of language evaluation and instruction.