Where was the JT17F number plate registered?

Vehicles with the JT17F prefix were first registered in the UK through official DVLA regional allocation tag JT.

What year was a JT17F registration plate released?

The JT17F series was issued during March 2017 to August 2017.

What is the MOT pass rate for JT17F vehicles?

Vehicles in the JT17F cohort demonstrate an average historical MOT pass rate of 87.5% based on 8 recorded DVSA inspections.

Batch Prefix Hub

JT17F Series Number Plates

UK vehicles during March 2017 to August 2017 with registration prefix JT17F.

Area Office: DVLA Region (JT)
Release Period: March 2017 to August 2017
Tracked in Batch: 2 vehicles
MOT Pass Rate: 87.5%

Popular Makes

BMW 50% (1)

MINI 50% (1)

87.5%

Average MOT Pass Rate

Based on 8 historical tests

Common Colors

Blue1 vehicles

Silver1 vehicles

Active Plates in JT17F Series(2 of 2 displayed)

Filter by 6th Letter:

JT17FEB

MOT Valid

MINI COOPER

1.5L · Petrol · Blue

First Used: Oct 2020
MOT Expiry: 06 Oct 2027
Tax Status: —
Color: Blue

Check History & Specs

JT17FLY

MOT Valid

BMW 330

2.0L · Hybrid Electric (Clean) · Silver

First Used: Apr 2017
MOT Expiry: 23 Nov 2026
Tax Status: —
Color: Silver

Check History & Specs

Reliability & Common Problem Guides for JT17F Makes

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

BMW Common Problems MINI Common Problems

Frequently Asked Questions about JT17F Plates

Where was the JT17F number plate series registered?

Vehicles starting with JT17F were assigned to the DVLA regional office covering the UK. The first two letters (JT) identify the memory tag assigned by the DVLA.

What registration period is JT17F?

The JT17F age identifier corresponds to vehicles first registered between March 2017 to August 2017.

How can I check the MOT history of a JT17F 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.