JiraForecast

JiraForecast – Probabilistic forecasting from real Jira data

JiraForecast (Data Center only) turns your team’s historical throughput into probabilistic delivery forecasts, directly from your Jira board or backlog page. Instead of guessing how long a batch of work will take, you can run Monte Carlo simulations on top of your actual completed issues and get realistic time ranges in seconds.

The extension reads the data from the active Jira board, reconstructs your daily, weekly and monthly throughput, and presents a clean dashboard with charts and statistics designed for agile teams.

Main features

- Historical throughput analysis
- Automatically extracts completed issues from the current Jira board.
- Rebuilds your throughput history (items per day/week/month).
- Use you current Quick Filters.
- Shows a bar chart of weekly throughput for the last weeks, with an average line to make trends obvious.
- Displays key sample statistics such as average items/day and several percentiles (P50, P80, P90, P95).
- Lead time / cycle time insights (optional section, depending on the board/control chart)
- Helps you understand how long items actually spend in your workflow.
- Visualizes the distribution of lead times in days, making long tails and outliers visible.

Monte Carlo forecasting

Lets you configure:
- Target (items) – how many issues you want to complete.
- Iterations – how many simulations to run.
- Max days – safety cap for very long simulations.

Runs Monte Carlo simulations by sampling from your historical throughput. Calculates forecast percentiles (P50, P80, P85, P90, P95) for the number of days needed to reach the target.

Shows results both as:

- Summary percentiles (P50, P80, etc.) in a compact “pill” layout.
- Histogram of days so you can see the shape of the forecast distribution.
- Visual, focused dashboard
- Dark theme that matches Jira nicely and makes charts easy to read.
- Clear separation between historical data, lead time, and Monte Carlo results.
- Designed for quick conversations with Product Owners, stakeholders and teams.

How it works

Open a Jira Software board or backlog page and click on the JiraForecast blue button on the top of the page.

Adjust the simulation parameters (target items, iterations, max days) and run Monte Carlo to get probabilistic delivery forecasts.

All calculations happen in your browser, on top of the data that Jira is already showing.

Permissions and data privacy

activeTab / scripting – used only to read the current Jira page and shows the button that opens JiraForecast.

storage – used to temporarily store the extracted data and pass it to the dashboard page inside the extension.

JiraForecast does not send your Jira data to any external server. All processing happens locally in the browser, and the data is only used for the purpose of computing and displaying the charts and simulations for you.

Who is it for?

Agile teams using Jira boards (Scrum or Kanban) that want more than simple velocity charts.

Product Owners, Delivery Managers and Scrum Masters who need realistic, data-driven answers to questions like “When will this batch of work be done?”

Anyone interested in using Monte Carlo simulations on top of real Jira history, without exporting data to spreadsheets or external tools.