Where was the UG08M number plate registered?

Vehicles with the UG08M prefix were first registered in the UK through official DVLA regional allocation tag UG.

What year was a UG08M registration plate released?

The UG08M series was issued during March 2008 to August 2008.

What is the MOT pass rate for UG08M vehicles?

Vehicles in the UG08M cohort demonstrate an average historical MOT pass rate of 90% based on 10 recorded DVSA inspections.

Batch Prefix Hub

UG08M Series Number Plates

UK vehicles during March 2008 to August 2008 with registration prefix UG08M.

Area Office: DVLA Region (UG)
Release Period: March 2008 to August 2008
Tracked in Batch: 2 vehicles
MOT Pass Rate: 90%

Popular Makes

HONDA 50% (1)

VOLKSWAGEN 50% (1)

90%

Average MOT Pass Rate

Based on 10 historical tests

Common Colors

Black1 vehicles

Grey1 vehicles

Active Plates in UG08M Series(2 of 2 displayed)

Filter by 6th Letter:

UG08MCR

MOT Valid

HONDA CIVIC

1.3L · Petrol · Grey

First Used: Jun 2008
MOT Expiry: 18 Nov 2026
Tax Status: —
Color: Grey

Check History & Specs

UG08MEG

MOT Valid

VOLKSWAGEN POLO

1.2L · Petrol · Black

First Used: Mar 2014
MOT Expiry: 31 Jul 2026
Tax Status: —
Color: Black

Check History & Specs

Reliability & Common Problem Guides for UG08M Makes

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

HONDA Common Problems VOLKSWAGEN Common Problems

Frequently Asked Questions about UG08M Plates

Where was the UG08M number plate series registered?

Vehicles starting with UG08M were assigned to the DVLA regional office covering the UK. The first two letters (UG) identify the memory tag assigned by the DVLA.

What registration period is UG08M?

The UG08M age identifier corresponds to vehicles first registered between March 2008 to August 2008.

How can I check the MOT history of a UG08M 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.