Jira Align is where enterprise agile organizations connect strategy to delivery. It rolls your teams’ work up into portfolio roadmaps, runs Program Increment (PI) planning, ties execution to OKRs, and makes dependencies visible across the whole organization. It is, rightly, the system of record for what you’re building and why.

But ask it one deceptively simple question — “what are the odds we actually hit this release date?” — and the answer it returns is a single projected date, not a probability. That isn’t a flaw in Jira Align; it’s simply a different job. And it’s exactly where Release Planning for Jira complements it.

What Jira Align does brilliantly

Before talking about gaps, give Jira Align its due. For organizations running SAFe or scaled agile, it delivers things no team-level tool can: a live portfolio roadmap, strategy-to-execution alignment, lean portfolio management, the PI planning program board, and dependency management across many teams at once. If you’ve invested in Jira Align, you did so for good reasons — and nothing here suggests undoing that. The goal is to make it sharper.

The one question it doesn’t answer: what are the odds?

Jira Align’s predicted delivery date is a deterministic calculation. Under the hood it takes the remaining work and divides it by an average rate — remaining estimate across your teams, or remaining story points divided by average velocity. The result is one date. (Jira Align once exposed a “Monte Carlo” setting for this; per Atlassian’s own documentation it is now a legacy option the platform no longer uses.)

A single average date is a useful planning signal but a shaky promise, for two everyday reasons:

• Velocity isn’t steady. Real teams speed up and slow down. An average quietly hides that variation, so a date built on it is right about as often as it’s wrong — with no warning either way.
• Story points are relative, not real numbers. A “2” isn’t reliably twice a “1.” Add up estimates, divide by an average, and you’ve baked guesswork straight into the deadline.

From a date to the odds: probabilistic release forecasting

Release Planning for Jira takes a different approach — the one banks and weather forecasters use to handle uncertainty: Monte Carlo simulation. Instead of a single date, it runs your remaining scope against your team’s real historical throughput thousands of times and reports the spread of outcomes as confidence levels.

So rather than “we’ll ship on December 12,” you get something you can actually stand behind: “85% chance we ship by December 12; 50% chance by the 4th.” Because it reads live Jira throughput — not story-point estimates — the forecast reflects how your teams genuinely deliver, and it updates itself as the work moves.

Complement, not replace

Here’s the important part: you don’t swap anything out. Jira Align stays your portfolio and PI planning backbone. Release Planning for Jira sits alongside it and feeds it better numbers — a confidence-based date you can carry into PI planning, and a fast cross-check when a rollup date looks too optimistic to be true.

It’s also a low-commitment addition. Jira Align is a significant enterprise platform; Release Planning for Jira is an affordable, native Forge app you can start with a free trial and have producing forecasts the same afternoon. Together they give leadership both halves of the picture: Jira Align confirms you’re building the right things, and Release Planning for Jira tells you the odds of delivering them on time.

One board for forecast, capacity, dependencies, and priorities

A date you can trust is far more useful when you can act on it in the same place, so Release Planning for Jira brings the planning levers together:

• Capacity-aware planning that accounts for PTO, public holidays, and work in progress — so forecasts reflect the team you’ll actually have next month.
• A drag-and-drop dependency graph with critical-path highlighting, so blockers surface before they derail a release.
• Built-in prioritization with WSJF, RICE, and MoSCoW to scope releases with intent.
• A “what-if” sandbox to test scope and timing changes without touching live Jira data.

Built on Atlassian Forge

Release Planning for Jira runs on Atlassian Forge, which means it carries the “Runs on Atlassian” badge: all compute and data stay inside Atlassian’s cloud and the app honors your data-residency region. If you chose Jira Align partly for governance and control, the forecasting layer holds the same line.

Who it’s for — and how to start

Product Managers, Product Owners, Release Train Engineers, and Delivery Leads get the most from it: anyone who has to stand up in PI planning (or in front of an executive) and put a credible date on a release. Install it next to your existing Jira Align setup and bring a probabilistic date into your very next planning session.

👉 Try Release Planning for Jira free on the Atlassian Marketplace

Want the technical version — how Jira Align computes dates, how Monte Carlo forecasting works, and how it feeds SAFe PI predictability? Read the technical guide for RTEs and Delivery Leads.