Aim: The purpose of this work is to identify the accuracy in prediction of air pollution during the lockdown. Materials and Methods: The research work contains two groups namely Predictive linear regression and Logistic regression. Each group consists of a sample size of 10 and the study parameters include an alpha value of 0.05, a beta value of 0.2, and a power value of 0.8. The performance analysis for maximum accuracy in the prediction of air pollution during lockdown using Predictive linear regression over Logistic regression which identifies and predicts the air pollution. Results and Discussion: The accuracy using Predictive linear regression is 98% is more accurate than the logistic regression of 92% in predicting air pollution. Conclusion: The Predictive linear regression model is significantly better than the logistic regression in predicting air pollution. It can also be considered a better option for predicting air pollution during the lockdown.