This paper provides prediction of air quality using computational intelligence techniques. The study employs various Computational Intelligence techniques to evaluate the data associated with environmental pollution and hence to predict the air quality focusing on PM2.5 and PM10 concentrations. The performance of each model is assessed with standard evaluation metrics. Through a series of simulations, it is observed that the results suggest that computational intelligence techniques play an essential role in improving the accuracy of air quality prediction models.