Where was the TJ64L number plate registered?

Vehicles with the TJ64L prefix were first registered in the UK through official DVLA regional allocation tag TJ.

What year was a TJ64L registration plate released?

The TJ64L series was issued during September 2014 to February 2015.

What is the MOT pass rate for TJ64L vehicles?

Vehicles in the TJ64L cohort demonstrate an average historical MOT pass rate of 70% based on 10 recorded DVSA inspections.

Batch Prefix Hub

TJ64L Series Number Plates

UK vehicles during September 2014 to February 2015 with registration prefix TJ64L.

Area Office: DVLA Region (TJ)
Release Period: September 2014 to February 2015
Tracked in Batch: 2 vehicles
MOT Pass Rate: 70%

Popular Makes

FORD 50% (1)

SEAT 50% (1)

70%

Average MOT Pass Rate

Based on 10 historical tests

Common Colors

White2 vehicles

Active Plates in TJ64L Series(2 of 2 displayed)

Filter by 6th Letter:

TJ64LEW

MOT Expired

FORD FIESTA

1.5L · Diesel · White

First Used: Sep 2014
MOT Expiry: 03 Apr 2025
Tax Status: —
Color: White

Check History & Specs

TJ64LOR

MOT Valid

SEAT IBIZA

1.4L · Petrol · White

First Used: Jan 2015
MOT Expiry: 15 Jan 2027
Tax Status: —
Color: White

Check History & Specs

Reliability & Common Problem Guides for TJ64L Makes

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

FORD Common Problems SEAT Common Problems

Frequently Asked Questions about TJ64L Plates

Where was the TJ64L number plate series registered?

Vehicles starting with TJ64L were assigned to the DVLA regional office covering the UK. The first two letters (TJ) identify the memory tag assigned by the DVLA.

What registration period is TJ64L?

The TJ64L age identifier corresponds to vehicles first registered between September 2014 to February 2015.

How can I check the MOT history of a TJ64L 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.