Where was the JG17K number plate registered?

Vehicles with the JG17K prefix were first registered in the UK through official DVLA regional allocation tag JG.

What year was a JG17K registration plate released?

The JG17K series was issued during March 2017 to August 2017.

What is the MOT pass rate for JG17K vehicles?

Vehicles in the JG17K cohort demonstrate an average historical MOT pass rate of 80% based on 10 recorded DVSA inspections.

Batch Prefix Hub

JG17K Series Number Plates

UK vehicles during March 2017 to August 2017 with registration prefix JG17K.

Area Office: DVLA Region (JG)
Release Period: March 2017 to August 2017
Tracked in Batch: 2 vehicles
MOT Pass Rate: 80%

Popular Makes

LAND ROVER 50% (1)

PEUGEOT 50% (1)

80%

Average MOT Pass Rate

Based on 10 historical tests

Common Colors

Grey2 vehicles

Active Plates in JG17K Series(2 of 2 displayed)

Filter by 6th Letter:

JG17KEL

MOT Valid

PEUGEOT 2008

1.6L · Diesel · Grey

First Used: Mar 2017
MOT Expiry: 23 Oct 2026
Tax Status: —
Color: Grey

Check History & Specs

JG17KTG

MOT Valid

LAND ROVER RANGE ROVER SPORT

3.0L · Diesel · Grey

First Used: Jun 2017
MOT Expiry: 28 Jun 2026
Tax Status: —
Color: Grey

Check History & Specs

Reliability & Common Problem Guides for JG17K Makes

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

LAND ROVER Common Problems PEUGEOT Common Problems

Frequently Asked Questions about JG17K Plates

Where was the JG17K number plate series registered?

Vehicles starting with JG17K 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 JG17K?

The JG17K age identifier corresponds to vehicles first registered between March 2017 to August 2017.

How can I check the MOT history of a JG17K 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.