Last updated: October 19, 2026
Toronto Crime Score is an independent reference site that assigns each of Toronto's 158 neighborhoods a safety score from 0 to 100, computed from official crime data published by the Toronto Police Service. The site is free to use, requires no account, and is refreshed whenever the source dataset is updated.
Every neighborhood receives a single score between 0 and 100, where lower is safer. The score combines nine crime categories - homicide, shooting, assault, robbery, break and enter, auto theft, theft over $5,000, theft from vehicle, and bicycle theft - so that neighborhoods of different sizes can be compared fairly. Scores fall into five bands:
The score describes relative levels of reported crime between neighborhoods. It is not a measure of any individual's personal risk.
The score is a severity-weighted sum of per-capita crime rates. For each of the nine categories:
The weighted points across all nine categories add up to the final score. Homicide carries the highest weight (35%), followed by shooting (25%), assault (12%), robbery (8%), break and enter (6%), auto theft (5%), theft over $5,000 (4%), theft from vehicle (3%), and bicycle theft (2%).
Crime counts come from the Toronto Police Service's Neighbourhood Crime Rates Open Data dataset on the Public Safety Data Portal, retrieved through its ArcGIS REST API (dataset endpoint). Neighborhood population figures are the projections published with that dataset, prepared by Environics Analytics.
The current release covers calendar year 2025 (annual rates), and the source dataset was last updated 2026-02-02.
Contains information licensed under the Open Government Licence - Ontario.
Toronto Crime Score is built and maintained by webuildstuff.io. It is not an official Toronto Police Service product, and the police service does not review or endorse the scores derived from its data.
Spotted an error or have a suggestion? Contact us - corrections are made when an official source supports the change. The site's source code is available on GitHub.