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Abstract: In order to save patients, doctors may be able to diagnose the victim and provide the correct anti-venom by recognising snakes by their bite marks. For doctors, aiding patients who have been bitten by snakes is a crucial step. Hence, research was conducted utilising CNN (Convolution Neural Network) model in Deep Learning methods to analyse photos and categorise them as belonging to various snake families. To categorise various snakes as venomous or non-poisonous snakes, the CNN model needs photographs of their bite marks. By analysing images of venomous snakes' bite markings, it is then able to identify the family of venomous snakes. The proposed deep learning model has to be trained repeatedly using all feasible distinct photos of the same snake family and various snake families in order to get correct results. The CNN model's effectiveness depends on its ability to recognise patterns in the input photos and identify the family of snakes. The method may take some time to provide results if the input photographs are many and large in size. It must be taken into account to provide outcomes with shorter execution times.