Where was the JV17R number plate registered?

Vehicles with the JV17R prefix were first registered in the UK through official DVLA regional allocation tag JV.

What year was a JV17R registration plate released?

The JV17R series was issued during March 2017 to August 2017.

What is the MOT pass rate for JV17R vehicles?

Vehicles in the JV17R cohort demonstrate an average historical MOT pass rate of 100% based on 10 recorded DVSA inspections.

Batch Prefix Hub

JV17R Series Number Plates

UK vehicles during March 2017 to August 2017 with registration prefix JV17R.

Area Office: DVLA Region (JV)
Release Period: March 2017 to August 2017
Tracked in Batch: 2 vehicles
MOT Pass Rate: 100%

Popular Makes

PORSCHE 50% (1)

SUZUKI 50% (1)

100%

Average MOT Pass Rate

Based on 10 historical tests

Common Colors

Blue1 vehicles

Red1 vehicles

Active Plates in JV17R Series(2 of 2 displayed)

Filter by 6th Letter:

JV17RDY

MOT Valid

PORSCHE macan

3.0L · Petrol · Blue

First Used: Mar 2018
MOT Expiry: 15 Jul 2027
Tax Status: —
Color: Blue

Check History & Specs

JV17RGO

MOT Valid

SUZUKI VITARA

1.6L · Petrol · Red

First Used: Apr 2018
MOT Expiry: 14 Feb 2027
Tax Status: —
Color: Red

Check History & Specs

Reliability & Common Problem Guides for JV17R Makes

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

PORSCHE Common Problems SUZUKI Common Problems

Frequently Asked Questions about JV17R Plates

Where was the JV17R number plate series registered?

Vehicles starting with JV17R were assigned to the DVLA regional office covering the UK. The first two letters (JV) identify the memory tag assigned by the DVLA.

What registration period is JV17R?

The JV17R age identifier corresponds to vehicles first registered between March 2017 to August 2017.

How can I check the MOT history of a JV17R 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.