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The episode of the Covid-19 infection in December 2019 in Wuhan has coverage crossways all around the planet by January 2020. The World Health Organization (WHO) named it has a Coronavirus and announced pandemic to stay away from the spreading of the infection. Since it is a profoundly infectious illness spreading quickly across all around the reality where the public authority of the multitude of impacted nations taken it has a main goal and confine the person to stay away from the spreading of the infection. The general manifestations of Coronavirus like dyspnoea, hack, influenza, breathing issue and fever. A portion of the patients are asymptotic however the RT-PCR results were positive, confident pathogenic challenging then confident CT pictures/X-Rays of the chest remain existence utilized to analyse the sickness. Profound Learning (DL) methods particularly Convolution Neural Network has effectively demonstrated for picture grouping and item discovery. CNN fundamentally utilized in picture examination assignments like picture recognition, object recognition and division. The proposed work utilizes H5-Keras model which is quite possibly the most well-known models for picture arrangement and the current model was additional tedious. The proposed model uses five districts in the lungs of Coronavirus patients and predicts whether or not the patient impacted with pneumonia and furthermore foreseeing the seriousness of the pneumonia. The proposed model uses CNN particularly H5-Keras model to analyse pneumonia for Coronavirus patients. Chest X-Ray informational collection is considered to prepare a CNN model for the analysis of Coronavirus sickness and to foresee pneumonia, seriousness of the pneumonia. Four unique intense CNN structures are explored on pictures of chest X-Rays aimed at conclusion of COVID-19 pneumonia. These copies take existed pre-arranged on the sequence-trial data base thus diminishing the prerequisite for colossal planning puts as they take pre-arranged loads. It was seen that CNN established designs could finding of COVID-19 pneumonia sickness with a superior precision.