Where was the TG64C number plate registered?

Vehicles with the TG64C prefix were first registered in the UK through official DVLA regional allocation tag TG.

What year was a TG64C registration plate released?

The TG64C series was issued during September 2014 to February 2015.

What is the MOT pass rate for TG64C vehicles?

Vehicles in the TG64C cohort demonstrate an average historical MOT pass rate of 100% based on 2 recorded DVSA inspections.

Batch Prefix Hub

TG64C Series Number Plates

UK vehicles during September 2014 to February 2015 with registration prefix TG64C.

Area Office: DVLA Region (TG)
Release Period: September 2014 to February 2015
Tracked in Batch: 2 vehicles
MOT Pass Rate: 100%

Popular Makes

FORD 100% (2)

100%

Average MOT Pass Rate

Based on 2 historical tests

Common Colors

Grey1 vehicles

Silver1 vehicles

Active Plates in TG64C Series(2 of 2 displayed)

Filter by 6th Letter:

TG64CDG

MOT Expired

FORD PUMA ST-LINE MHEV

Hybrid Electric (Clean) · Grey

First Used: Jun 2025
MOT Expiry: —
Tax Status: —
Color: Grey

Check History & Specs

TG64CJG

MOT Valid

FORD ECOSPORT

1.0L · Petrol · Silver

First Used: Sep 2021
MOT Expiry: 31 Aug 2026
Tax Status: —
Color: Silver

Check History & Specs

Reliability & Common Problem Guides for TG64C Makes

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

FORD Common Problems

Frequently Asked Questions about TG64C Plates

Where was the TG64C number plate series registered?

Vehicles starting with TG64C were assigned to the DVLA regional office covering the UK. The first two letters (TG) identify the memory tag assigned by the DVLA.

What registration period is TG64C?

The TG64C age identifier corresponds to vehicles first registered between September 2014 to February 2015.

How can I check the MOT history of a TG64C 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.