Eawfgtuw Electric Scooter Front Fork Aluminum Alloy Wheel Bracket Replacement Accessory Compatible with For Xiaomi 4 Pro, Long LastingBlack Fork

• Electric Scooter Front Fork: Replacement aluminum alloy front fork compatible with For Xiaomi 4 Pro electric scooter, designed for quick and secure installation to restore optimal ride performance; includes wheel bracket assembly for seamless integration
• Compatible With For Xiaomi 4 Pro: -engineered fork ensures exact fitment and alignment with original frame geometry; maintains scooter balance and steering control for safer, smoother rides on private property use only
• Aluminum Alloy Construction: Lightweight yet long lasting material provides high strength-to-weight ratio; resists wear and Erosion under regular use; weighs approximately 680g with compact 340*82mm dimensions for Suitable support
• Front Wheel Bracket Integration: Features integrated mounting points for wheel axle and suspension components; engineered mechanism enhances stability and shock absorption, improving handling over uneven surfaces
• Enhanced Ride Stability: Upgraded fork design improves directional control and For response during operation; outcome is more confident riding experience with reduced wobble; always follow local regulations—use restricted to private land with owner permission

: It is to ride electric scooters on public roads, pavements, or cycle paths. They are intended only for use on private land with the owner's permission Features: * and *Made of Quality material, and practical to use *For Easy and quick to install, used to replace the old broken scooter fork *Fit for xiaomi 4 Pro Electric Scooter Specifications: *Product Name:Electric Scooter Front Fork for xiaomi 4Pro *Material:Aluminum alloy *Size:340*82mm *Color:Black *Weight: About 680g Package Content: x Front Fork Note: . The real color of the item may be slightly different from the pictures shown on website caused by many factors such as brightness of your and light brightness. 2. Please allow slight manual measurement deviation for the data.