Where was the TK14J number plate registered?

Vehicles with the TK14J prefix were first registered in the UK through official DVLA regional allocation tag TK.

What year was a TK14J registration plate released?

The TK14J series was issued during March 2014 to August 2014.

What is the MOT pass rate for TK14J vehicles?

Vehicles in the TK14J cohort demonstrate an average historical MOT pass rate of 80% based on 5 recorded DVSA inspections.

Batch Prefix Hub

TK14J Series Number Plates

UK vehicles during March 2014 to August 2014 with registration prefix TK14J.

Area Office: DVLA Region (TK)
Release Period: March 2014 to August 2014
Tracked in Batch: 2 vehicles
MOT Pass Rate: 80%

Popular Makes

FORD 50% (1)

MAZDA 50% (1)

80%

Average MOT Pass Rate

Based on 5 historical tests

Common Colors

Black1 vehicles

Blue1 vehicles

Active Plates in TK14J Series(2 of 2 displayed)

Filter by 6th Letter:

TK14JAY

MOT Valid

MAZDA CX-5

2.2L · Diesel · Blue

First Used: Dec 2014
MOT Expiry: 09 Dec 2026
Tax Status: —
Color: Blue

Check History & Specs

TK14JON

MOT Expired

FORD RANGER RAPTOR ECOBLUE 4X4 AUTO

Diesel · Black

First Used: Oct 2023
MOT Expiry: —
Tax Status: —
Color: Black

Check History & Specs

Reliability & Common Problem Guides for TK14J Makes

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

FORD Common Problems MAZDA Common Problems

Frequently Asked Questions about TK14J Plates

Where was the TK14J number plate series registered?

Vehicles starting with TK14J were assigned to the DVLA regional office covering the UK. The first two letters (TK) identify the memory tag assigned by the DVLA.

What registration period is TK14J?

The TK14J age identifier corresponds to vehicles first registered between March 2014 to August 2014.

How can I check the MOT history of a TK14J 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.