Where was the JR66B number plate registered?

Vehicles with the JR66B prefix were first registered in the UK through official DVLA regional allocation tag JR.

What year was a JR66B registration plate released?

The JR66B series was issued during September 2016 to February 2017.

What is the MOT pass rate for JR66B vehicles?

Vehicles in the JR66B cohort demonstrate an average historical MOT pass rate of 90% based on 10 recorded DVSA inspections.

Batch Prefix Hub

JR66B Series Number Plates

UK vehicles during September 2016 to February 2017 with registration prefix JR66B.

Area Office: DVLA Region (JR)
Release Period: September 2016 to February 2017
Tracked in Batch: 2 vehicles
MOT Pass Rate: 90%

Popular Makes

BMW 50% (1)

JEEP 50% (1)

90%

Average MOT Pass Rate

Based on 10 historical tests

Common Colors

Black1 vehicles

Red1 vehicles

Active Plates in JR66B Series(2 of 2 displayed)

Filter by 6th Letter:

JR66BEN

MOT Valid

JEEP RENEGADE

1.6L · Diesel · Black

First Used: Sep 2016
MOT Expiry: 06 Feb 2027
Tax Status: —
Color: Black

Check History & Specs

JR66BMW

MOT Valid

BMW X3

3.0L · Diesel · Red

First Used: Sep 2016
MOT Expiry: 05 Oct 2026
Tax Status: —
Color: Red

Check History & Specs

Reliability & Common Problem Guides for JR66B Makes

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

BMW Common Problems JEEP Common Problems

Frequently Asked Questions about JR66B Plates

Where was the JR66B number plate series registered?

Vehicles starting with JR66B were assigned to the DVLA regional office covering the UK. The first two letters (JR) identify the memory tag assigned by the DVLA.

What registration period is JR66B?

The JR66B age identifier corresponds to vehicles first registered between September 2016 to February 2017.

How can I check the MOT history of a JR66B 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.