Where was the XM66H number plate registered?

Vehicles with the XM66H prefix were first registered in Personal Export through official DVLA regional allocation tag XM.

What year was a XM66H registration plate released?

The XM66H series was issued during September 2016 to February 2017.

What is the MOT pass rate for XM66H vehicles?

Vehicles in the XM66H cohort demonstrate an average historical MOT pass rate of 80% based on 10 recorded DVSA inspections.

Batch Prefix Hub

XM66H Series Number Plates

UK vehicles registered in Personal Export during September 2016 to February 2017 with registration prefix XM66H.

Area Office: Personal Export (Personal Export)
Release Period: September 2016 to February 2017
Tracked in Batch: 2 vehicles
MOT Pass Rate: 80%

Popular Makes

BMW 100% (2)

80%

Average MOT Pass Rate

Based on 10 historical tests

Common Colors

Black1 vehicles

Grey1 vehicles

Active Plates in XM66H Series(2 of 2 displayed)

XM66HAL

MOT Valid

BMW 430

3.0L · Diesel · Black

First Used: Dec 2016
MOT Expiry: 14 Mar 2027
Tax Status: —
Color: Black

Check History & Specs

XM66HAY

MOT Valid

BMW X6

4.4L · Petrol · Grey

First Used: May 2017
MOT Expiry: 09 Apr 2027
Tax Status: —
Color: Grey

Check History & Specs

Reliability & Common Problem Guides for XM66H Makes

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

BMW Common Problems

Frequently Asked Questions about XM66H Plates

Where was the XM66H number plate series registered?

Vehicles starting with XM66H were assigned to the Personal Export covering Personal Export. The first two letters (XM) identify the memory tag assigned by the DVLA.

What registration period is XM66H?

The XM66H age identifier corresponds to vehicles first registered between September 2016 to February 2017.

How can I check the MOT history of a XM66H 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.