Ford Recalls Transit Connect
Ford Motor Company issued a recall for select 2016-2017 model-year Ford Transit Connect vehicles. In affected vehicles, the driver and/or front passenger seat belt pretensioners may not deploy in a crash event in which the front seat belt pretensioners are activated.
The recall
affects 1,616 vehicles in the United States and 131 in Canada. Affected vehicles were built at Valencia Assembly Plant, July 17-31, 2016.
Photo: Ford
Ford Motor Company issued a recall for select 2016-2017 model-year Ford Transit Connect vehicles. In affected vehicles, the driver and/or front passenger seat belt pretensioners may not deploy in a crash event in which the front seat belt pretensioners are activated.
Even with the primary seat belt locking function operating properly, if the front seat belt pretensioner fails to deploy during a crash, it may increase the risk of injury to a front occupant. Ford is not aware of any such non-deployments or injuries associated with this condition.
This action affects 1,616 vehicles in the United States and 131 in Canada. Affected vehicles were built at Valencia Assembly Plant, July 17-31, 2016.
Dealers will inspect the driver and front passenger seat belt assemblies and replace those that were produced during the suspect date range. The Ford reference number for this recall is 20S25.
Originally posted on Work Truck Online
More Safety
Managing Road Risk at Scale: Why Fleet Safety Needs a Data-Driven Framework
Insights from the FIA Road and Driver Safety Indexes reveal how to manage road risk on a larger scale.
Read More →
Stellantis Recalls 1.3 Million Jeep Vehicles Worldwide Over Fire Risk
Stellantis is recalling more than 1.3 million Jeep Wrangler and Gladiator models worldwide over a fire risk linked to power steering pump wiring.
Read More →
Coaching Is Not Training, Even When AI Is Doing It
AI-powered safety platforms can detect risky behaviors and deliver immediate feedback. But effective driver development still requires a foundation of training followed by coaching that reinforces those skills.
Read More →
How Emotions Behind the Wheel Can Affect Fleet Safety
During National Safety Month, fleets are encouraged to look beyond distracted driving and recognize how stress, fatigue, and emotional well-being influence driver performance and crash risk.
Read More →
Nominations Open for 2026 Fleet Safety Award
Nominations have officially opened for the 2026 Fleet Safety Award Winner.
Read More →
Turning Connected Vehicle Data Into Decisions That Matter
Fleet leaders have more data than ever, but turning that data into clear, actionable decisions remains a challenge. This white paper shows how leading organizations are using connected vehicle data to improve safety, reduce costs, and optimize fleet performance. Learn how to turn insight into action across your fleet.
Read More →
Cameras, Safety and Insurance: From Reactive Claims to Real-time Prevention
Commercial auto remains one of the most challenging and costly lines of coverage for fleet operators and insurers alike. Learn more about how to effectively address these issues from Onur Aksan, Enterprise Business Development Executive, Geotab.
Read More →
NAFA Fleet Safety Symposium to Collocate With 2026 Fleet Forward Conference
The daylong certificate program will precede the Fleet Forward Conference at the Gaylord National Harbor in Maryland.
Read More →
The Distractions You Can’t Turn Off: What Drivers Face Outside the Vehicle
Fleet drivers face constant visual, cognitive, and environmental interruptions the moment they hit the road. From roadside chaos to mental fatigue and digital overload, today’s biggest driving risks often come from outside the vehicle itself.
Read More →
FLASH Weather AI Launches First Deep-Learning Hail Prediction Model With High-Resolution Forecasting
FLASH Weather AI has launched a first-of-its-kind hail prediction model capable of forecasting hail size and arrival time at 1-kilometer resolution up to 55 minutes ahead, giving fleets and insurers critical time to prepare for severe storms.
Read More →