Sex trafficking is an international crisis that has permeated the online realm, enabling traffickers to build a larger client base and evade law enforcement. The current study was conducted to identify sex trafficking by comparing advertisements (ads) with matching contact information. Ads with matching contact information and different descriptions of individuals may signify that one individual is controlling the sale of multiple people, potentially indicating trafficking. A customized web scraper was utilized to collect information from ads from the ‘personals’ category of Leolist.cc; those with social media handles, phone/WhatsApp numbers, email addresses, and ‘click to view’ numbers were extracted. Ads were grouped based on matching contact information and qualitatively analyzed; groups with different physical descriptions of girls were coded as potential trafficking. Ads with matching contacts and listings of multiple girls were searched with sex trafficking keywords and coded as potential trafficking or agency if at least half the ads contained over three keywords. From 7,328 unique contacts, 97 were coded as potential trafficking and 67 as potential trafficking or agency. The practical implication of this project is that an automated tool may be developed that uses these methods to identify trafficking advertisements to take them down, potentially aiding victims.