Where was the JG16N number plate registered?

Vehicles with the JG16N prefix were first registered in the UK through official DVLA regional allocation tag JG.

What year was a JG16N registration plate released?

The JG16N series was issued during March 2016 to August 2016.

What is the MOT pass rate for JG16N vehicles?

Vehicles in the JG16N cohort demonstrate an average historical MOT pass rate of 66.7% based on 3 recorded DVSA inspections.

Batch Prefix Hub

JG16N Series Number Plates

UK vehicles during March 2016 to August 2016 with registration prefix JG16N.

Area Office: DVLA Region (JG)
Release Period: March 2016 to August 2016
Tracked in Batch: 2 vehicles
MOT Pass Rate: 66.7%

Popular Makes

TOYOTA 100% (2)

66.7%

Average MOT Pass Rate

Based on 3 historical tests

Common Colors

Orange1 vehicles

Red1 vehicles

Active Plates in JG16N Series(2 of 2 displayed)

Filter by 6th Letter:

JG16NAN

MOT Valid

TOYOTA HILUX INVINCIB X D-4D4WD DCB A

2.8L · Diesel · Orange

First Used: May 2023
MOT Expiry: 19 Feb 2027
Tax Status: —
Color: Orange

Check History & Specs

JG16NJG

MOT Expired

TOYOTA C-HR

1.8L · Hybrid Electric (Clean) · Red

First Used: Sep 2018
MOT Expiry: 07 Jul 2023
Tax Status: —
Color: Red

Check History & Specs

Reliability & Common Problem Guides for JG16N Makes

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

TOYOTA Common Problems

Frequently Asked Questions about JG16N Plates

Where was the JG16N number plate series registered?

Vehicles starting with JG16N were assigned to the DVLA regional office covering the UK. The first two letters (JG) identify the memory tag assigned by the DVLA.

What registration period is JG16N?

The JG16N age identifier corresponds to vehicles first registered between March 2016 to August 2016.

How can I check the MOT history of a JG16N 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.