JD16M Series Number Plates
UK vehicles during March 2016 to August 2016 with registration prefix JD16M.
- Area Office
- DVLA Region (JD)
- Release Period
- March 2016 to August 2016
- Tracked in Batch
- 8 vehicles
- MOT Pass Rate
- 89.3%
Average MOT Pass Rate
Based on 28 historical tests
Common Colors
Active Plates in JD16M Series(8 of 8 displayed)
FORD KUGA
2.0L · Diesel · Blue
- First Used
- Mar 2016
- MOT Expiry
- 18 Feb 2027
- Tax Status
- —
- Color
- Blue
NISSAN NAVARA
2.3L · Diesel · Grey
- First Used
- Sep 2020
- MOT Expiry
- 08 Sep 2026
- Tax Status
- —
- Color
- Grey
MITSUBISHI L200
2.4L · Diesel · Red
- First Used
- Mar 2016
- MOT Expiry
- 29 Mar 2027
- Tax Status
- —
- Color
- Red
BMW 420
2.0L · Petrol · Blue
- First Used
- Jul 2016
- MOT Expiry
- 27 Jun 2026
- Tax Status
- —
- Color
- Blue
BMW R 1200
1.2L · Petrol · Black
- First Used
- May 2016
- MOT Expiry
- 02 May 2027
- Tax Status
- —
- Color
- Black
FORD KUGA
1.5L · Diesel · Grey
- First Used
- Sep 2018
- MOT Expiry
- 22 Sep 2026
- Tax Status
- —
- Color
- Grey
FORD ECOSPORT
1.5L · Petrol · White
- First Used
- Sep 2016
- MOT Expiry
- 03 Nov 2026
- Tax Status
- —
- Color
- White
MAZDA MX-5
2.0L · Petrol · Red
- First Used
- Mar 2016
- MOT Expiry
- 28 Feb 2027
- Tax Status
- —
- Color
- Red
Reliability & Common Problem Guides for JD16M Makes
Explore common mechanical faults, MOT advisory trends, and recall notices for popular vehicles in this registration batch:
Frequently Asked Questions about JD16M Plates
Where was the JD16M number plate series registered?
Vehicles starting with JD16M were assigned to the DVLA regional office covering the UK. The first two letters (JD) identify the memory tag assigned by the DVLA.
What registration period is JD16M?
The JD16M age identifier corresponds to vehicles first registered between March 2016 to August 2016.
How can I check the MOT history of a JD16M 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.