Where was the JU03V number plate registered?

Vehicles with the JU03V prefix were first registered in the UK through official DVLA regional allocation tag JU.

What year was a JU03V registration plate released?

The JU03V series was issued during March 2003 to August 2003.

What is the MOT pass rate for JU03V vehicles?

Vehicles in the JU03V cohort demonstrate an average historical MOT pass rate of 80% based on 10 recorded DVSA inspections.

Batch Prefix Hub

JU03V Series Number Plates

UK vehicles during March 2003 to August 2003 with registration prefix JU03V.

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

Popular Makes

FORD 50% (1)

NISSAN 50% (1)

80%

Average MOT Pass Rate

Based on 10 historical tests

Common Colors

Black1 vehicles

White1 vehicles

Active Plates in JU03V Series(2 of 2 displayed)

Filter by 6th Letter:

JU03VAS

MOT Valid

NISSAN QASHQAI

1.5L · Diesel · White

First Used: Jun 2019
MOT Expiry: 12 Apr 2027
Tax Status: —
Color: White

Check History & Specs

JU03VVV

MOT Valid

FORD FOCUS

1.6L · Petrol · Black

First Used: Sep 2009
MOT Expiry: 22 Jan 2027
Tax Status: —
Color: Black

Check History & Specs

Reliability & Common Problem Guides for JU03V Makes

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

FORD Common Problems NISSAN Common Problems

Frequently Asked Questions about JU03V Plates

Where was the JU03V number plate series registered?

Vehicles starting with JU03V were assigned to the DVLA regional office covering the UK. The first two letters (JU) identify the memory tag assigned by the DVLA.

What registration period is JU03V?

The JU03V age identifier corresponds to vehicles first registered between March 2003 to August 2003.

How can I check the MOT history of a JU03V 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.