Where was the JX03N number plate registered?

Vehicles with the JX03N prefix were first registered in the UK through official DVLA regional allocation tag JX.

What year was a JX03N registration plate released?

The JX03N series was issued during March 2003 to August 2003.

What is the MOT pass rate for JX03N vehicles?

Vehicles in the JX03N cohort demonstrate an average historical MOT pass rate of 80% based on 10 recorded DVSA inspections.

Batch Prefix Hub

JX03N Series Number Plates

UK vehicles during March 2003 to August 2003 with registration prefix JX03N.

Area Office: DVLA Region (JX)
Release Period: March 2003 to August 2003
Tracked in Batch: 2 vehicles
MOT Pass Rate: 80%

Popular Makes

AUDI 50% (1)

VOLKSWAGEN 50% (1)

80%

Average MOT Pass Rate

Based on 10 historical tests

Common Colors

Grey1 vehicles

White1 vehicles

Active Plates in JX03N Series(2 of 2 displayed)

Filter by 6th Letter:

JX03NBX

MOT Valid

AUDI Q5

2.0L · Diesel · White

First Used: Sep 2014
MOT Expiry: 19 Apr 2027
Tax Status: —
Color: White

Check History & Specs

JX03NET

MOT Valid

VOLKSWAGEN GOLF

1.4L · Petrol · Grey

First Used: Mar 2017
MOT Expiry: 16 Feb 2027
Tax Status: —
Color: Grey

Check History & Specs

Reliability & Common Problem Guides for JX03N Makes

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

AUDI Common Problems VOLKSWAGEN Common Problems

Frequently Asked Questions about JX03N Plates

Where was the JX03N number plate series registered?

Vehicles starting with JX03N were assigned to the DVLA regional office covering the UK. The first two letters (JX) identify the memory tag assigned by the DVLA.

What registration period is JX03N?

The JX03N age identifier corresponds to vehicles first registered between March 2003 to August 2003.

How can I check the MOT history of a JX03N 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.