Where was the JU66C number plate registered?

Vehicles with the JU66C prefix were first registered in the UK through official DVLA regional allocation tag JU.

What year was a JU66C registration plate released?

The JU66C series was issued during September 2016 to February 2017.

What is the MOT pass rate for JU66C vehicles?

Vehicles in the JU66C cohort demonstrate an average historical MOT pass rate of 100% based on 5 recorded DVSA inspections.

Batch Prefix Hub

JU66C Series Number Plates

UK vehicles during September 2016 to February 2017 with registration prefix JU66C.

Area Office: DVLA Region (JU)
Release Period: September 2016 to February 2017
Tracked in Batch: 2 vehicles
MOT Pass Rate: 100%

Popular Makes

AUDI 50% (1)

FORD 50% (1)

100%

Average MOT Pass Rate

Based on 5 historical tests

Common Colors

Blue1 vehicles

White1 vehicles

Active Plates in JU66C Series(2 of 2 displayed)

Filter by 6th Letter:

JU66CAB

MOT Expired

AUDI A1

Petrol · White

First Used: May 2025
MOT Expiry: —
Tax Status: —
Color: White

Check History & Specs

JU66CHR

MOT Valid

FORD FOCUS

2.3L · Petrol · Blue

First Used: Nov 2016
MOT Expiry: 01 Nov 2026
Tax Status: —
Color: Blue

Check History & Specs

Reliability & Common Problem Guides for JU66C Makes

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

AUDI Common Problems FORD Common Problems

Frequently Asked Questions about JU66C Plates

Where was the JU66C number plate series registered?

Vehicles starting with JU66C were assigned to the DVLA regional office covering the UK. The first two letters (JU) identify the memory tag assigned by the DVLA.

What registration period is JU66C?

The JU66C age identifier corresponds to vehicles first registered between September 2016 to February 2017.

How can I check the MOT history of a JU66C 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.