Where was the JW60V number plate registered?

Vehicles with the JW60V prefix were first registered in the UK through official DVLA regional allocation tag JW.

What year was a JW60V registration plate released?

The JW60V series was issued during September 2010 to February 2011.

What is the MOT pass rate for JW60V vehicles?

Vehicles in the JW60V cohort demonstrate an average historical MOT pass rate of 77.8% based on 9 recorded DVSA inspections.

Batch Prefix Hub

JW60V Series Number Plates

UK vehicles during September 2010 to February 2011 with registration prefix JW60V.

Area Office: DVLA Region (JW)
Release Period: September 2010 to February 2011
Tracked in Batch: 2 vehicles
MOT Pass Rate: 77.8%

Popular Makes

KIA 50% (1)

TOYOTA 50% (1)

77.8%

Average MOT Pass Rate

Based on 9 historical tests

Common Colors

White2 vehicles

Active Plates in JW60V Series(2 of 2 displayed)

Filter by 6th Letter:

JW60VEG

MOT Valid

TOYOTA AYGO

1.0L · Petrol · White

First Used: Jun 2011
MOT Expiry: 03 Dec 2026
Tax Status: —
Color: White

Check History & Specs

JW60VJW

MOT Valid

KIA STONIC

1.0L · Petrol · White

First Used: Jun 2018
MOT Expiry: 10 May 2027
Tax Status: —
Color: White

Check History & Specs

Reliability & Common Problem Guides for JW60V Makes

Explore common mechanical faults, MOT advisory trends, and recall notices for popular vehicles in this registration batch:

KIA Common Problems TOYOTA Common Problems

Frequently Asked Questions about JW60V Plates

Where was the JW60V number plate series registered?

Vehicles starting with JW60V were assigned to the DVLA regional office covering the UK. The first two letters (JW) identify the memory tag assigned by the DVLA.

What registration period is JW60V?

The JW60V age identifier corresponds to vehicles first registered between September 2010 to February 2011.

How can I check the MOT history of a JW60V vehicle?

Click any registration in the plate list above to view the complete DVSA inspection history, advisory alerts, mileage progression, road tax status, and our AI mechanical risk evaluation.