Where was the JG04Y number plate registered?

Vehicles with the JG04Y prefix were first registered in the UK through official DVLA regional allocation tag JG.

What year was a JG04Y registration plate released?

The JG04Y series was issued during March 2004 to August 2004.

What is the MOT pass rate for JG04Y vehicles?

Vehicles in the JG04Y cohort demonstrate an average historical MOT pass rate of 66.7% based on 9 recorded DVSA inspections.

Batch Prefix Hub

JG04Y Series Number Plates

UK vehicles during March 2004 to August 2004 with registration prefix JG04Y.

Area Office: DVLA Region (JG)
Release Period: March 2004 to August 2004
Tracked in Batch: 2 vehicles
MOT Pass Rate: 66.7%

JG04Y Cohort Statistics

Popular Makes

JAGUAR 50% (1)

YAMAHA50% (1)

66.7%

Average MOT Pass Rate

Based on 9 historical tests

Common Colors

Black1 vehicles

Grey1 vehicles

Active Plates in JG04Y Series(2 of 2 displayed)

Filter by 6th Letter:

JG04YAM

MOT Valid

YAMAHA MT 125 ABS

0.1L · Petrol · Grey

First Used: Apr 2019
MOT Expiry: 13 May 2026
Tax Status: —
Color: Grey

Check History & Specs

JG04YSG

MOT Valid

JAGUAR XE

2.0L · Diesel · Black

First Used: Mar 2017
MOT Expiry: 02 Mar 2027
Tax Status: —
Color: Black

Check History & Specs

Reliability & Common Problem Guides for JG04Y Makes

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

JAGUAR Common Problems

Frequently Asked Questions about JG04Y Plates

Where was the JG04Y number plate series registered?

Vehicles starting with JG04Y were assigned to the DVLA regional office covering the UK. The first two letters (JG) identify the memory tag assigned by the DVLA.

What registration period is JG04Y?

The JG04Y age identifier corresponds to vehicles first registered between March 2004 to August 2004.

How can I check the MOT history of a JG04Y 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.