Where was the UF07P number plate registered?

Vehicles with the UF07P prefix were first registered in the UK through official DVLA regional allocation tag UF.

What year was a UF07P registration plate released?

The UF07P series was issued during March 2007 to August 2007.

What is the MOT pass rate for UF07P vehicles?

Vehicles in the UF07P cohort demonstrate an average historical MOT pass rate of 70% based on 10 recorded DVSA inspections.

Batch Prefix Hub

UF07P Series Number Plates

UK vehicles during March 2007 to August 2007 with registration prefix UF07P.

Area Office: DVLA Region (UF)
Release Period: March 2007 to August 2007
Tracked in Batch: 2 vehicles
MOT Pass Rate: 70%

Popular Makes

FORD 50% (1)

SKODA 50% (1)

70%

Average MOT Pass Rate

Based on 10 historical tests

Common Colors

Orange1 vehicles

PURPLE1 vehicles

Active Plates in UF07P Series(2 of 2 displayed)

UF07PAM

MOT Valid

FORD KUGA

2.0L · Diesel · Orange

First Used: Nov 2015
MOT Expiry: 08 Feb 2027
Tax Status: —
Color: Orange

Check History & Specs

UF07PAW

MOT Valid

SKODA SUPERB S GREENLINE II TDI

1.6L · Diesel · PURPLE

First Used: Nov 2012
MOT Expiry: 04 Jun 2027
Tax Status: —
Color: PURPLE

Check History & Specs

Reliability & Common Problem Guides for UF07P Makes

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

FORD Common Problems SKODA Common Problems

Frequently Asked Questions about UF07P Plates

Where was the UF07P number plate series registered?

Vehicles starting with UF07P were assigned to the DVLA regional office covering the UK. The first two letters (UF) identify the memory tag assigned by the DVLA.

What registration period is UF07P?

The UF07P age identifier corresponds to vehicles first registered between March 2007 to August 2007.

How can I check the MOT history of a UF07P 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.