Where was the UD16M number plate registered?

Vehicles with the UD16M prefix were first registered in the UK through official DVLA regional allocation tag UD.

What year was a UD16M registration plate released?

The UD16M series was issued during March 2016 to August 2016.

What is the MOT pass rate for UD16M vehicles?

Vehicles in the UD16M cohort demonstrate an average historical MOT pass rate of 100% based on 10 recorded DVSA inspections.

Batch Prefix Hub

UD16M Series Number Plates

UK vehicles during March 2016 to August 2016 with registration prefix UD16M.

Area Office: DVLA Region (UD)
Release Period: March 2016 to August 2016
Tracked in Batch: 2 vehicles
MOT Pass Rate: 100%

Popular Makes

MAZDA 50% (1)

NISSAN 50% (1)

100%

Average MOT Pass Rate

Based on 10 historical tests

Common Colors

Red1 vehicles

Silver1 vehicles

Active Plates in UD16M Series(2 of 2 displayed)

Filter by 6th Letter:

UD16MPH

MOT Valid

NISSAN NAVARA

2.3L · Diesel · Silver

First Used: Apr 2016
MOT Expiry: 05 Nov 2026
Tax Status: —
Color: Silver

Check History & Specs

UD16MUD

MOT Valid

MAZDA cx-3

2.0L · Petrol · Red

First Used: Jan 2017
MOT Expiry: 27 Dec 2026
Tax Status: —
Color: Red

Check History & Specs

Reliability & Common Problem Guides for UD16M Makes

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

MAZDA Common Problems NISSAN Common Problems

Frequently Asked Questions about UD16M Plates

Where was the UD16M number plate series registered?

Vehicles starting with UD16M were assigned to the DVLA regional office covering the UK. The first two letters (UD) identify the memory tag assigned by the DVLA.

What registration period is UD16M?

The UD16M age identifier corresponds to vehicles first registered between March 2016 to August 2016.

How can I check the MOT history of a UD16M 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.