Where was the JL14U number plate registered?

Vehicles with the JL14U prefix were first registered in the UK through official DVLA regional allocation tag JL.

What year was a JL14U registration plate released?

The JL14U series was issued during March 2014 to August 2014.

What is the MOT pass rate for JL14U vehicles?

Vehicles in the JL14U cohort demonstrate an average historical MOT pass rate of 88.9% based on 9 recorded DVSA inspections.

Batch Prefix Hub

JL14U Series Number Plates

UK vehicles during March 2014 to August 2014 with registration prefix JL14U.

Area Office: DVLA Region (JL)
Release Period: March 2014 to August 2014
Tracked in Batch: 2 vehicles
MOT Pass Rate: 88.9%

Popular Makes

AUDI 50% (1)

FORD 50% (1)

88.9%

Average MOT Pass Rate

Based on 9 historical tests

Common Colors

Black1 vehicles

Grey1 vehicles

Active Plates in JL14U Series(2 of 2 displayed)

Filter by 6th Letter:

JL14UND

MOT Valid

FORD RANGER

3.2L · Diesel · Grey

First Used: Mar 2019
MOT Expiry: 12 Apr 2027
Tax Status: —
Color: Grey

Check History & Specs

JL14URA

MOT Valid

AUDI E-TRON TECHNIK 50 QUATTRO

Electric · Black

First Used: Aug 2020
MOT Expiry: 17 Feb 2027
Tax Status: —
Color: Black

Check History & Specs

Reliability & Common Problem Guides for JL14U Makes

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

AUDI Common Problems FORD Common Problems

Frequently Asked Questions about JL14U Plates

Where was the JL14U number plate series registered?

Vehicles starting with JL14U were assigned to the DVLA regional office covering the UK. The first two letters (JL) identify the memory tag assigned by the DVLA.

What registration period is JL14U?

The JL14U age identifier corresponds to vehicles first registered between March 2014 to August 2014.

How can I check the MOT history of a JL14U 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.