---
title: "Curve Fitting Calculator"
description: "Fit a curve to your data online. Paste X/Y points and run linear, polynomial, exponential, logarithmic, power, logistic, Gaussian, or custom regression — with coefficients, R-squared, RMSE, and an interactive chart. Runs entirely in your browser."
url: https://findutils.com/calculate/curve-fitting-calculator/
category: calculate
---

# Curve Fitting Calculator

Fit a curve to your data online. Paste X/Y points and run linear, polynomial, exponential, logarithmic, power, logistic, Gaussian, or custom regression — with coefficients, R-squared, RMSE, and an interactive chart. Runs entirely in your browser.

**Use this tool:** [Curve Fitting Calculator](https://findutils.com/calculate/curve-fitting-calculator/)

## Programmatic access

- Browser-only: this tool works on a file, the DOM, or a browser API and has no REST or MCP id.

## Why use a curve fitting calculator?

Curve fitting finds the equation that best describes the relationship between two variables. Instead of guessing a trendline by eye, this tool solves for the coefficients that minimize the error between your data and a chosen model — linear, polynomial, exponential, logarithmic, power, logistic, Gaussian, or any custom equation you type. You get the fitted equation, the R-squared and RMSE that tell you how well it fits, and a chart that overlays the curve on your points. Everything runs locally in your browser, so your data never leaves your device.

## Frequently Asked Questions

### What is curve fitting?

Curve fitting finds the equation that best matches a set of X/Y data points. The calculator solves for the coefficients of your chosen model so the curve passes as close as possible to every point.

### What does R-squared mean?

R-squared (the coefficient of determination) measures how well the fitted curve explains the variation in your data. It ranges from 0 to 1 — a value near 1 means the model fits closely, while a low value means the model is a poor match.

### Which model should I choose?

Pick the shape that matches your data: a line for steady trends, a polynomial for smooth curves, exponential or power for growth and decay, logarithmic for diminishing returns, logistic for an S-shaped saturation, and Gaussian for a single peak. If none fit, enter a custom equation.

### Can I fit my own equation?

Yes. Choose 'Custom equation' and type any expression using x and single-letter parameters such as a b, and c — for example a*sin(b*x) + c. The optimizer will solve for the parameter values that best fit your data.

### Is my data uploaded anywhere?

No. All calculations happen entirely in your browser. Your data points are never sent to a server.

### Why did my fit fail to converge?

Nonlinear fits depend on a reasonable starting point and well-behaved data. Try a different model, remove outliers, or rescale very large or very small values. Exponential, power, and logarithmic models also require positive values in places.

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