Political science is a science, but not in the same way physics or chemistry is. It uses the scientific method, tests hypotheses with data, and builds theories meant to explain real-world phenomena. But it operates under constraints that make it fundamentally different from the natural sciences: its subject matter is human behavior, which is far less predictable than molecules or planets. The honest answer is that political science sits in a middle ground, and whether you consider it a “real” science depends on what standard you’re applying.
What Makes Something a Science
The scientific method rests on three principles: observations must be empirical (based on real-world data, not speculation), the process must be transparent (others can see exactly what you did), and results must be replicable (someone else following the same steps should reach similar findings). Political science follows all three. Researchers articulate a clear question, review existing literature, build a theory, construct testable hypotheses, gather data, analyze it, and publish their results for others to scrutinize.
Political scientists test whether relationships exist between variables the same way a biologist might test whether a drug affects cell growth. The difference is in what they’re measuring. A biologist can isolate a cell in a controlled environment. A political scientist studying voter behavior can’t isolate a voter from the economy, media coverage, personal identity, and a thousand other influences all operating at once.
Where Political Science Falls Short of the Natural Sciences
The biggest gap is experimental control. Natural sciences rely heavily on experiments where subjects are randomly assigned to groups and researchers can manipulate one variable at a time to measure its effect. Political science rarely has that luxury. You can’t randomly assign countries to adopt different constitutions to see which one produces more stability. You can’t rerun an election with one variable changed. Some political scientists do run controlled experiments (especially in survey research and behavioral studies), but these are far less common than in fields like biology or chemistry.
Then there’s the problem of consensus. In the natural sciences, researchers largely agree on which concepts matter, how to define them, and how to measure them. Political science has far less agreement on all three fronts. What does “democracy” mean, exactly? How do you measure “political power”? Reasonable scholars define and measure these things differently, which means they can study the same question and reach different conclusions not because one is wrong, but because they’re measuring slightly different things.
Measurement error compounds this problem. Even when political scientists agree on definitions and methods, their measurements are inherently less precise. Asking people how they voted introduces memory bias, social desirability bias, and simple dishonesty in ways that measuring the boiling point of water does not.
The result is that political science produces tendencies rather than laws. Newton’s laws of motion predict with extraordinary accuracy what will happen when a force acts on an object. Political science can tell you that democracies tend not to go to war with each other, or that economic downturns tend to hurt incumbent parties. “Tend to” is doing a lot of work in those sentences. People don’t behave as predictably as molecules.
What Political Science Can Actually Predict
Despite those limitations, political science does generate genuine predictive knowledge. Election forecasting is a useful test case. Analysis of the American National Election Studies surveys from 1952 to 2020 found that pre-election voter intention measures predicted the actual popular vote outcome with reasonable accuracy, off by about 2.23 percentage points on average. That’s not perfect, but it’s far from random guessing. The catch: forecasting the popular vote doesn’t always reveal the actual winner, as several recent U.S. elections have demonstrated.
Beyond elections, political scientists use sophisticated quantitative tools. Statistical modeling, probability theory, and formal mathematical approaches like game theory allow researchers to model voting behavior, legislative bargaining, lobbying dynamics, and even the conditions under which violent conflict breaks out. Columbia University’s political science program, for instance, applies game theory to study repeated interactions between political actors, incomplete information in negotiations, and strategic decision-making in auctions and institutional design. These aren’t just abstract exercises. They produce testable predictions about how political actors will behave under specific conditions.
The Debate Within the Field
Political scientists themselves disagree about how scientific their discipline should try to be. In 2000, an anonymous letter signed “Mr. Perestroika” sparked a movement within the American Political Science Association, arguing that the field had become too narrow in its methods. The complaint was that the discipline’s leading journal had become dominated by quantitative, statistics-heavy research at the expense of historical analysis, case studies, interpretive approaches, and qualitative work. The movement called the discipline’s focus “methodological parochialism.”
This wasn’t a fringe complaint. Multiple prominent scholars agreed that political science had tried too hard to mimic the natural sciences, and in doing so had sidelined approaches that were better suited to understanding politics in its full complexity. The tension persists today. Some political scientists build mathematical models and run regression analyses. Others write deeply researched case studies of single countries or events. Both camps claim to be doing rigorous work, and both have a point.
The Philosophical Question Underneath
The philosopher Karl Popper argued that scientific theories must be falsifiable: they must make predictions that could, in principle, be proven wrong. By this standard, some political science theories qualify and some don’t. A model predicting that a specific set of economic conditions will lead to an incumbent party losing an election is falsifiable. You can check. A vague claim that “power corrupts” is not, because it doesn’t specify conditions under which it would be proven false.
Popper himself took aim at one of the most ambitious claims in political science: that we can discover “laws of history” and use them to predict the future of societies the way astronomers predict eclipses. He argued this was a fundamental misunderstanding of how science works. Even in the natural sciences, prediction depends on controlled, repeatable conditions. Societies aren’t controlled or repeatable. Popper specifically criticized Marxism as a political theory that had started out making genuinely testable predictions, then retreated into unfalsifiable territory by adding explanations after the fact whenever its predictions failed.
This doesn’t disqualify all of political science. It does mean that political science theories exist on a spectrum of scientific rigor, and the field as a whole can’t claim the same predictive precision as physics or chemistry.
How Institutions Classify It
Major scientific institutions treat political science as a legitimate science, if a distinct kind. The U.S. National Science Foundation has funded political science research through its Directorate for Social, Behavioral and Economic Sciences. Universities worldwide house political science in their colleges of arts and sciences alongside biology and physics, not in their humanities departments alongside literature and philosophy. The field grants PhDs, publishes in peer-reviewed journals, and requires training in research methods and statistics.
The classification “social science” is itself the most precise answer. Political science is a science of human social behavior. It uses scientific methods adapted to the reality that people are more complicated, less predictable, and harder to study in controlled settings than atoms or chemical reactions. It produces real knowledge, backed by evidence, that holds up to scrutiny. It just can’t promise the kind of certainty that the word “science” implies when most people hear it.