Where was the JP13V number plate registered?

Vehicles with the JP13V prefix were first registered in the UK through official DVLA regional allocation tag JP.

What year was a JP13V registration plate released?

The JP13V series was issued during March 2013 to August 2013.

What is the MOT pass rate for JP13V vehicles?

Vehicles in the JP13V cohort demonstrate an average historical MOT pass rate of 80% based on 5 recorded DVSA inspections.

Batch Prefix Hub

JP13V Series Number Plates

UK vehicles during March 2013 to August 2013 with registration prefix JP13V.

Area Office: DVLA Region (JP)
Release Period: March 2013 to August 2013
Tracked in Batch: 2 vehicles
MOT Pass Rate: 80%

Popular Makes

JAGUAR 50% (1)

SKODA 50% (1)

80%

Average MOT Pass Rate

Based on 5 historical tests

Common Colors

Black1 vehicles

Grey1 vehicles

Active Plates in JP13V Series(2 of 2 displayed)

Filter by 6th Letter:

JP13VER

MOT Expired

SKODA KODIAQ SE L EXECUTIVE TSI S-A

Petrol · Black

First Used: Jul 2023
MOT Expiry: —
Tax Status: —
Color: Black

Check History & Specs

JP13VVV

MOT Valid

JAGUAR XF

2.0L · Diesel · Grey

First Used: Sep 2015
MOT Expiry: 05 Aug 2027
Tax Status: —
Color: Grey

Check History & Specs

Reliability & Common Problem Guides for JP13V Makes

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

JAGUAR Common Problems SKODA Common Problems

Frequently Asked Questions about JP13V Plates

Where was the JP13V number plate series registered?

Vehicles starting with JP13V were assigned to the DVLA regional office covering the UK. The first two letters (JP) identify the memory tag assigned by the DVLA.

What registration period is JP13V?

The JP13V age identifier corresponds to vehicles first registered between March 2013 to August 2013.

How can I check the MOT history of a JP13V 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.