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Abstract: As we know, now a days the quality of air decreasing day by day and is very harmful for humans. Before going to outside of home it is now necessary to know the quality of air to take the necessary precautions. The AQI of a particular area is a measure of pollutants mixed in air of the respected region. As per the air quality standard pollutants are indexed in terms of their scale, these air quality indexes indicates the levels of major pollutants mixed in the atmosphere. Today, major cities experience levels of air pollution that are dangerously higher than the government-set air quality index standard. It significantly affects a person's health. The Machine Learning (ML) algorithms are capable of making predictions about air pollution. We are here to check the air quality index of a particular area to find air pollution level in that area. The classifiers used in our project are Random Forest Regressor. The measured results of our experiments show that the Random Forest Regressor algorithm outperforms other algorithms, and that it reaches the highest accuracy not only in air quality prediction, but also in other detection systems.