Currently there are many machine learning models that have been deployed to predict whether if a person will default their loan amount or they will pay it back. These decisions are made using predictive modelling and ML by using various factors of the person, such as their education level, sex, personal status, checking amount, number of savings bonds and many more. The aim of this project to use one of such publicly available datasets, the Statlog - German Credit Risk Dataset which has anonymized data of many customers of a bank, with their personal details and whether if they had defaulted their loan amount or they were good customers and paid back their loan amount. Within this project I aim to first pre-process the data into both user readable and machine readable format, explore the data and derive inferences, and finally use this to predict whether if a person will default their loan or not.