In the UK, house price estimation is an important topic. It has been discussed in numerous academic research publications and official and business reports. A house’s price can change depending on size, age, and location. One of the main characteristics of a property’s neighbourhood is the crime rate; it is crucial to consider how it may affect the home’s price. If crime rates rise, a neighbourhood may lose appeal to potential purchasers in favour of comparable-priced neighbourhoods. This study employs data from January 2020 to April 2022 to examine the relationship between crime rates and house prices in Bristol, UK. Crime datasets were taken from the UK Crime Stats website, while data on house prices was taken from the Price Paid Data of the HM Land Registry. 34,000 transaction records and criminal statistics are combined in the study to provide a comprehensive dataset for analysis. Two tree-based machine learning algorithms-Decision Tree (DT) and Random Forest (RF)-and Exploratory Data Analysis (EDA) were used to model and evaluate the data. The results show that the Random Forest outperformed the Decision Tree regarding prediction accuracy. According to the results, there is a substantial correlation between crime rates and house prices. While vehicle crimes and bike theft had a positive correlation with property values, violent crimes had the opposite effect. These revelations highlight the intricate relationship between different kinds of crime and the characteristics of the housing market, with considerable consequences for investors, policymakers, and real estate developers.

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