Where was the JG17E number plate registered?

Vehicles with the JG17E prefix were first registered in the UK through official DVLA regional allocation tag JG.

What year was a JG17E registration plate released?

The JG17E series was issued during March 2017 to August 2017.

What is the MOT pass rate for JG17E vehicles?

Vehicles in the JG17E cohort demonstrate an average historical MOT pass rate of 90% based on 10 recorded DVSA inspections.

Batch Prefix Hub

JG17E Series Number Plates

UK vehicles during March 2017 to August 2017 with registration prefix JG17E.

Area Office: DVLA Region (JG)
Release Period: March 2017 to August 2017
Tracked in Batch: 2 vehicles
MOT Pass Rate: 90%

JG17E Cohort Statistics

Popular Makes

BMW 50% (1)

SEAT 50% (1)

90%

Average MOT Pass Rate

Based on 10 historical tests

Common Colors

Blue1 vehicles

White1 vehicles

Active Plates in JG17E Series(2 of 2 displayed)

Filter by 6th Letter:

JG17EMG

MOT Valid

BMW X1

2.0L · Diesel · White

First Used: Mar 2017
MOT Expiry: 02 Mar 2027
Tax Status: —
Color: White

Check History & Specs

JG17ENS

MOT Valid

SEAT LEON

1.4L · Petrol · Blue

First Used: Apr 2018
MOT Expiry: 05 Apr 2027
Tax Status: —
Color: Blue

Check History & Specs

Reliability & Common Problem Guides for JG17E Makes

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

BMW Common Problems SEAT Common Problems

Frequently Asked Questions about JG17E Plates

Where was the JG17E number plate series registered?

Vehicles starting with JG17E 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 JG17E?

The JG17E age identifier corresponds to vehicles first registered between March 2017 to August 2017.

How can I check the MOT history of a JG17E 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.