Anyone who read Nassim Nicholas Taleb’s bestseller The Black Swan will probably regard the global financial meltdown as proof of Taleb’s point. He argued that it’s not the normal events—the mundane and expected “white swans”—that drive socioeconomic history but the magnificent outliers, the completely unexpected “black swans.” Think September 11, 2001, or the invention of the internet. Human history pivots on the rare seismic shifts that no one predicts or even has a chance of predicting.

In recent months, we’ve seen the real estate bust, the implosion of hedge funds, and the demise of investment-banking giants like Lehman Brothers, Merrill Lynch, and Bear Stearns. Surely this economic collapse was a black swan, as unpredictable as it was rare?

Maybe not.

A small but growing cadre of scientists are arguing that our current crisis was in fact predictable and that the technology exists to make sure that it won’t happen again. The problem may be that we’ve used only economists to try to solve our economic predicaments. Instead, the solution may be found by physicists and other scientists accustomed to studying complex systems.

To anticipate the next crisis and find our way out of this one, we may have to cast off economic and financial dogma and adopt ideas inspired by physics and other natural sciences, disciplines in which the notion of unstable and unpredictable systems is nothing new. For instance, the technology now exists to go beyond economics to build a massive, complete computer model of the modern economy, from the corner store to the city bank and the Federal Reserve.

With such a model, physicists would be able to track changes in the economy dynamically. There have even been calls for an ambitious effort akin to the Manhattan Project, which built the atomic bomb, to bring the most sophisticated mathematics and computer modeling to bear on managing the world’s economies more aggressively than has ever been attempted.

Some of the work has already begun. When the state of Illinois decided to deregulate its electricity market, it wanted to avoid the disastrous outcome California suffered after Enron Corp. manipulated prices, created shortages, and spurred rolling blackouts. So the state hired scientists at Argonne National Laboratories to build a sophisticated model of Illinois’ power market, incorporating suppliers, consumers, regulators, and the like. The model showed that Illinois’ initial market design was vulnerable to Enron-like manipulation. Having learned this lesson in virtual reality, the state was able to change its approach before embarking on deregulation in the real world. The state made its changes and so far has avoided even a hint of California-style problems.

Generally, economists have been loath to use such techniques. “We’re not currently using the best capabilities of science,” says physicist Dirk Helbing, who leads a new division devoted to social modeling at the Swiss Federal Institute of Technology in Zurich. “We need to bring together scientists from different fields and put together tools that can be used as a kind of wind tunnel for testing out social and economic policies.”

The idea is that by studying so-called complex systems—traffic flow, ecosystems, organisms, weather—we can begin to make sense of an increasingly unpredictable economic world. Didier Sornette, for instance, is a world expert on earthquakes. Now he’s heading up a lab in Zurich called the Financial Crisis Observatory, examining how frothy markets show the same signs of stress that the earth shows before an earthquake. Sornette’s group is trying to develop the ability to provide economic warnings, in part by monitoring the stocks of the 500 largest U.S. companies.

In addition, the group has studied the real estate market in hopes of finding signs of coming collapse. By looking at the prices of new homes sold in the U.S. in 2005, the group’s models predicted the bubble that eventually formed, particularly in the Northeast and the West.