Where was the JN16W number plate registered?

Vehicles with the JN16W prefix were first registered in the UK through official DVLA regional allocation tag JN.

What year was a JN16W registration plate released?

The JN16W series was issued during March 2016 to August 2016.

What is the MOT pass rate for JN16W vehicles?

Vehicles in the JN16W cohort demonstrate an average historical MOT pass rate of 70% based on 10 recorded DVSA inspections.

Batch Prefix Hub

JN16W Series Number Plates

UK vehicles during March 2016 to August 2016 with registration prefix JN16W.

Area Office: DVLA Region (JN)
Release Period: March 2016 to August 2016
Tracked in Batch: 2 vehicles
MOT Pass Rate: 70%

Popular Makes

FIAT 50% (1)

LAND ROVER 50% (1)

70%

Average MOT Pass Rate

Based on 10 historical tests

Common Colors

Red1 vehicles

White1 vehicles

Active Plates in JN16W Series(2 of 2 displayed)

Filter by 6th Letter:

JN16WAN

MOT Valid

LAND ROVER DISCOVERY SPORT

2.0L · Diesel · Red

First Used: Mar 2016
MOT Expiry: 28 Feb 2027
Tax Status: —
Color: Red

Check History & Specs

JN16WEN

MOT Valid

FIAT 500

1.2L · Petrol · White

First Used: Aug 2016
MOT Expiry: 07 Oct 2026
Tax Status: —
Color: White

Check History & Specs

Reliability & Common Problem Guides for JN16W Makes

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

FIAT Common Problems LAND ROVER Common Problems

Frequently Asked Questions about JN16W Plates

Where was the JN16W number plate series registered?

Vehicles starting with JN16W were assigned to the DVLA regional office covering the UK. The first two letters (JN) identify the memory tag assigned by the DVLA.

What registration period is JN16W?

The JN16W age identifier corresponds to vehicles first registered between March 2016 to August 2016.

How can I check the MOT history of a JN16W 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.