Where was the JT17C number plate registered?

Vehicles with the JT17C prefix were first registered in the UK through official DVLA regional allocation tag JT.

What year was a JT17C registration plate released?

The JT17C series was issued during March 2017 to August 2017.

What is the MOT pass rate for JT17C vehicles?

Vehicles in the JT17C cohort demonstrate an average historical MOT pass rate of 100% based on 4 recorded DVSA inspections.

Batch Prefix Hub

JT17C Series Number Plates

UK vehicles during March 2017 to August 2017 with registration prefix JT17C.

Area Office: DVLA Region (JT)
Release Period: March 2017 to August 2017
Tracked in Batch: 2 vehicles
MOT Pass Rate: 100%

Popular Makes

HYUNDAI 50% (1)

SEAT 50% (1)

100%

Average MOT Pass Rate

Based on 4 historical tests

Common Colors

Blue1 vehicles

Red1 vehicles

Active Plates in JT17C Series(2 of 2 displayed)

Filter by 6th Letter:

JT17CAM

MOT Valid

HYUNDAI I30

1.4L · Petrol · Blue

First Used: Sep 2019
MOT Expiry: 29 Sep 2026
Tax Status: —
Color: Blue

Check History & Specs

JT17CMT

MOT Expired

SEAT IBIZA XCELLENCE ECOTSI S-A

Petrol · Red

First Used: May 2025
MOT Expiry: —
Tax Status: —
Color: Red

Check History & Specs

Reliability & Common Problem Guides for JT17C Makes

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

HYUNDAI Common Problems SEAT Common Problems

Frequently Asked Questions about JT17C Plates

Where was the JT17C number plate series registered?

Vehicles starting with JT17C 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 JT17C?

The JT17C age identifier corresponds to vehicles first registered between March 2017 to August 2017.

How can I check the MOT history of a JT17C 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.