Where was the JX57M number plate registered?

Vehicles with the JX57M prefix were first registered in the UK through official DVLA regional allocation tag JX.

What year was a JX57M registration plate released?

The JX57M series was issued during September 2007 to February 2008.

What is the MOT pass rate for JX57M vehicles?

Vehicles in the JX57M cohort demonstrate an average historical MOT pass rate of 100% based on 5 recorded DVSA inspections.

Batch Prefix Hub

JX57M Series Number Plates

UK vehicles during September 2007 to February 2008 with registration prefix JX57M.

Area Office: DVLA Region (JX)
Release Period: September 2007 to February 2008
Tracked in Batch: 2 vehicles
MOT Pass Rate: 100%

Popular Makes

AUDI 50% (1)

MAZDA 50% (1)

100%

Average MOT Pass Rate

Based on 5 historical tests

Common Colors

Blue1 vehicles

Grey1 vehicles

Active Plates in JX57M Series(2 of 2 displayed)

Filter by 6th Letter:

JX57MAC

MOT Expired

MAZDA CX-30 HOMURA MHEV

Petrol · Blue

First Used: Apr 2025
MOT Expiry: —
Tax Status: —
Color: Blue

Check History & Specs

JX57MCG

MOT Valid

AUDI A5

1.4L · Petrol · Grey

First Used: Nov 2018
MOT Expiry: 16 Jul 2027
Tax Status: —
Color: Grey

Check History & Specs

Reliability & Common Problem Guides for JX57M Makes

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

AUDI Common Problems MAZDA Common Problems

Frequently Asked Questions about JX57M Plates

Where was the JX57M number plate series registered?

Vehicles starting with JX57M were assigned to the DVLA regional office covering the UK. The first two letters (JX) identify the memory tag assigned by the DVLA.

What registration period is JX57M?

The JX57M age identifier corresponds to vehicles first registered between September 2007 to February 2008.

How can I check the MOT history of a JX57M 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.