Where was the TN16L number plate registered?

Vehicles with the TN16L prefix were first registered in the UK through official DVLA regional allocation tag TN.

What year was a TN16L registration plate released?

The TN16L series was issued during March 2016 to August 2016.

What is the MOT pass rate for TN16L vehicles?

Vehicles in the TN16L cohort demonstrate an average historical MOT pass rate of 100% based on 5 recorded DVSA inspections.

Batch Prefix Hub

TN16L Series Number Plates

UK vehicles during March 2016 to August 2016 with registration prefix TN16L.

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

Popular Makes

MERCEDES-BENZ 50% (1)

MINI 50% (1)

100%

Average MOT Pass Rate

Based on 5 historical tests

Common Colors

Black1 vehicles

Blue1 vehicles

Active Plates in TN16L Series(2 of 2 displayed)

TN16LES

MOT Valid

MINI COOPER

1.5L · Petrol · Blue

First Used: Mar 2019
MOT Expiry: 28 Mar 2027
Tax Status: —
Color: Blue

Check History & Specs

TN16LEY

MOT Expired

MERCEDES-BENZ AMG C 43 NIGHT ED PREM + 4M A

Petrol · Black

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

Check History & Specs

Reliability & Common Problem Guides for TN16L Makes

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

MERCEDES-BENZ Common Problems MINI Common Problems

Frequently Asked Questions about TN16L Plates

Where was the TN16L number plate series registered?

Vehicles starting with TN16L were assigned to the DVLA regional office covering the UK. The first two letters (TN) identify the memory tag assigned by the DVLA.

What registration period is TN16L?

The TN16L age identifier corresponds to vehicles first registered between March 2016 to August 2016.

How can I check the MOT history of a TN16L 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.