Trump Travel Ban and the Visa Bulletin: What It Actually Means for Your Green Card
Posted by CM | June 2026 | Labels: Trump Policy, Visa Bulletin, Predictions
We are now squarely in Q3 of FY2026, and the June 2026 Visa Bulletin (Chart A) has handed us a mixed bag. EB-2 India took the most painful hit — a -10.5 month retrogression. EB-1 India also slid back -3.5 months. The one bright spot is EB-3 India creeping forward by +1 month and EB-3 China by +1.5 months. Note that Chart B remains suspended — so USCIS is using Chart A dates for all filing and approval purposes this month. Data source: DOS Visa Bulletin June 2026, and my own tracking spreadsheet going back to FY2020.
TL;DR — June 2026 Snapshot + July Predictions
| Category | Current (Jun 2026) | Predicted (Jul 2026) | Signal |
|---|---|---|---|
| EB-1 India | 15 Dec 2022 | 01 Dec 2022 | High Retrogression Risk |
| EB-2 India | 01 Sep 2013 | 15 Oct 2013 | Slight Recovery Possible |
| EB-3 India | 15 Dec 2013 | 15 Jan 2014 | Slow Advance |
| EB-1 China | 01 Apr 2023 | 15 Apr 2023 | Modest Advance |
| EB-2 China | 01 Sep 2021 | 01 Nov 2021 | Benefiting from Ban |
| EB-3 China | 01 Aug 2021 | 15 Sep 2021 | Advancing |
Bottom line: The travel ban is compressing EB-1 India via retrogression while paradoxically opening space in China and ROW categories — visa recapture logic is the key mechanism here.
Now layer on top of this the Trump travel ban covering approximately 40 countries. This is not a minor footnote. When nationals of banned countries — many of whom are in the ROW (rest of world) bucket or hold dual nationalities — cannot enter the US or cannot complete consular processing, their visa numbers go unused. The question everyone is asking me is: where do those unused numbers go? The answer, as I will walk through below, has direct consequences for your priority date.
I want to be upfront that we are in a gray area here. USCIS and DOS have not published a clear mechanism explaining how ban-related visa number savings are being redistributed. What I am offering below is an educated guess based on historical spillover behavior, current VB velocity data, and the Trump boost multiplier I have been applying in my model — currently at 1.25x for categories that appear to be indirectly absorbing freed-up numbers.