Outcome-based education is currently recommended in every field of education by the accreditation bodies. Outcome-based education is the process of developing the curriculum in a well-defined framework. The stated outcome or the instructional objective should be properly defined for successful implementation. Here, a methodology is proposed where the curriculum designer can check whether the instructional objective is properly designed. The methodology consists of website development and a machine learning model (ML) using natural language processing. The input to the model is an instructional objective statement, and the result will be in three categories: poor, good, and perfect. The website consists of a Flask-written backend and a Next. js-developed frontend. The backend was integrated with the ML model. For the model, the Bidirectional Encoder Representations from Transformers model is used. The designed model was applied to 50 instructional objective datasets for training the model and 40 datasets for testing the prediction. The BERT model was found to be effective.