The Forecasting Principles site summarizes all useful knowledge about forecasting so that it can be used by researchers, practitioners, and educators. (Those who might want to challenge this are invited to submit missing information.) This knowledge is provided as principles (guidelines, prescriptions, rules, conditions, action statements, or advice about what to do in given situations).

Principles of Forecasting: A Handbook for Researchers and PractionersThis site describes all evidenced-based principles on forecasting and provides sources to support the principles. The primary source is Principles of Forecasting, a comprehensive summary of forecasting knowledge which involved 40 authors and 123 reviewers.

Site Guidelines

The directors of forecastingprinciples.com use the following guidelines to help achieve the site’s objectives:

1. Open

Include all submitted evidence relevant to forecasting principles that meets scientific standards (objectivity, full disclosure of methods and data, and clear writing).

2. Useful

Provide information and materials likely to be helpful to practitioners, teachers and researchers.

3. Timely

List new information as soon as it becomes available.

4. Objective

Rely on evidence rather than on opinions. Avoid puffery and endorsing particular products.

5. Understandable

Ensure that normal human beings can make sense of the site’s content.

6. Civil

Maintain a courteous tone.

7. Free

Provide core content as a public service.


The Forecasting Principles site is provided as a public service by the International Institute of Forecasters. A companion site provides information about the Institute, the International Symposium on Forecasting, the International Journal of Forecasting, and Foresight: The International Journal of Applied Forecasting. Support for this site was initially provided by the Marketing Department of the Wharton School.

How To Use this Site

  • The Navigation Bar at the top of each page contains nine resources:

    • Methodology Tree - describes methods and show how they are related to one another. This Tree will also link you to further information.
    • Selection Tree - guides you to the most effective forecasting method for a given problem. More generally, the Selection Tree provides one way to navigate the site by focusing on methodological issues.
    • Forecasting Audit - allows you to identify weak areas of your forecasting system.
    • The Principles – "Standards and Practices for Forecasting" describes the original 139 forecasting principles, and the purpose, conditions, and evidence for each.
    • Forecasting Canon – or "Nine Generalizations to Improve Forecast Accuracy" provides a gentle introduction to evidence-based forecasting and the opportunity for large gains for those who follow them.
    • Forecasting Dictionary - defines key forecasting words or phrases, often with links to related concepts and relevant research.
    • FAQ – or Frequently Asked Questions, pose and answer questions that are often asked about forecasting; you may be surprised by some of the answers.
    • Site Map - gives an overview of the site and has links to all key pages.
    • Site Search - allows you to search for key words or phrases on pages throughout this site. You will find this at the top of each page.
  • For a computer translation of this site, please use the links in the main menu. If your language is not in the list, we suggest you use the URL mode of such sites as Prompt Online's IM Translator - if you type or copy the url for this site (i.e., forecastingprinciples.com) into the prompt box and select the language you wish to translate into (English-Spanish), the IM Translator will not only translate this entire home page for you, but all links you follow will likewise be translated.


Forecastingprinciples.com was created in 1997 by:

Dr J. Scott Armstrong, Professor at the Wharton School, University of Pennsylvania, Philadelphia, PA 19104, founded ForPrin.com in 1997. He has been a Director since that time.

Scott is included in a 2010 list of the 25 Most Famous College Professors Teaching Today.

Fred Collopy interviewed Scott for the International Journal of Forecasting in 2011. In the interview, Scott discusses his contributions to and thoughts about forecasting (available here).

Alain Elkann interviews famous people. An April 2015 Alain Elkann Interview with Scott discusses how his approach to science produces so many contrarian findings.





Dr Kesten Green 2

Dr Kesten C. Green of the University of South Australia Business School and Ehrenberg-Bass Institute, joined him in 2006 as co-director.

Kesten developed the simulated interaction and structured analogies methods for forecasting decisions in conflict situations such as business competition, union-management disputes, mergers and acquisitions, diplomacy, terrorism, and warfare. He champions the importance of using evidence-based forecasting methods to guide public policy decisions, such as for climate change.

Kesten is a co-originator of the Golden Rule of Forecasting. His findings on superior predictive validity of sophisticatedly simple forecasting methods over complex ones challenge current enthusiasms for big data analytics.

Kesten hasn't always been an academic, but forecasting has always been important for him. Before joining the University of South Australia late in 2009, he was a founder and director of a twice-weekly horse race forecasting publisher, an economic forecasting and consulting house, and a market research business.




Changes are made on a regular basis, usually many changes each week. The date of the last important revision to each page is at the bottom of the left-hand navigation bar.

Awards for this Site

  • "Award of Excellence" from StudySphere (June 21, 2006).
  • Rated at 4 stars (out of five) on the MERLOT site on October 2005
  • Listed among Best Information on the Net sites by the O'Keefe Library of St. Ambrose University.
  • Named as one of the top 5% of DSS sites by Decision Support Systems Resources.
  • Rated with 4 checks (out of five) on the Argus Clearinghouse, under Statistics.