  There is an evident lack of implementation of Machine Learning (ML) in the
legal domain in India, and any research that does take place in this domain is
usually based on data from the higher courts of law and works with English
data. The lower courts and data from the different regional languages of India
are often overlooked. In this paper, we deploy a Convolutional Neural Network
(CNN) architecture on a corpus of Hindi legal documents. We perform a bail
Prediction task with the help of a CNN model and achieve an overall accuracy of
93\% which is an improvement on the benchmark accuracy, set by Kapoor et al.
(2022), albeit in data from 20 districts of the Indian state of Uttar Pradesh.
