Where was the JJ71C number plate registered?

Vehicles with the JJ71C prefix were first registered in the UK through official DVLA regional allocation tag JJ.

What year was a JJ71C registration plate released?

The JJ71C series was issued during September 2021 to February 2022.

What is the MOT pass rate for JJ71C vehicles?

Vehicles in the JJ71C cohort demonstrate an average historical MOT pass rate of 100% based on 4 recorded DVSA inspections.

Batch Prefix Hub

JJ71C Series Number Plates

UK vehicles during September 2021 to February 2022 with registration prefix JJ71C.

Area Office: DVLA Region (JJ)
Release Period: September 2021 to February 2022
Tracked in Batch: 2 vehicles
MOT Pass Rate: 100%

Popular Makes

FORD 50% (1)

LAND ROVER 50% (1)

100%

Average MOT Pass Rate

Based on 4 historical tests

Common Colors

Black2 vehicles

Active Plates in JJ71C Series(2 of 2 displayed)

JJ71CAL

MOT Valid

FORD PUMA ST

1.5L · Petrol · Black

First Used: May 2022
MOT Expiry: 07 May 2027
Tax Status: —
Color: Black

Check History & Specs

JJ71CAM

MOT Valid

LAND ROVER RANGE ROVER SPORT

5.0L · Petrol · Black

First Used: Dec 2021
MOT Expiry: 04 Aug 2027
Tax Status: —
Color: Black

Check History & Specs

Reliability & Common Problem Guides for JJ71C Makes

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

FORD Common Problems LAND ROVER Common Problems

Frequently Asked Questions about JJ71C Plates

Where was the JJ71C number plate series registered?

Vehicles starting with JJ71C were assigned to the DVLA regional office covering the UK. The first two letters (JJ) identify the memory tag assigned by the DVLA.

What registration period is JJ71C?

The JJ71C age identifier corresponds to vehicles first registered between September 2021 to February 2022.

How can I check the MOT history of a JJ71C 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.