Merlin Bird ID by Cornell Lab

What's that bird? Ask Merlin—the world’s leading app for birds. Just like magic, Merlin Bird ID will help you solve the mystery.
Merlin Bird ID helps you identify birds you see and hear. Merlin is unlike any other bird app—it's powered by eBird, the world’s largest database of bird sightings, sounds, and photos.
Merlin offers four fun ways to identify birds. Answer a few simple questions, upload a photo, record a singing bird, or explore birds in a region.
Whether you’re curious about a bird you’ve seen once or you’re hoping to identify every bird you can find, the answers are waiting for you with this free app from the renowned Cornell Lab of Ornithology.
WHY YOU’LL LOVE MERLIN
• Expert ID tips, range maps, photos, and sounds help you learn about the birds you spot and build birding skills.
• Discover a new bird species each day with your own personalized Bird of the Day
• Get customized lists of birds you can find where you live or travel - anywhere in the world!
• Keep track of your sightings—build your personal list of the birds you find
MACHINE LEARNING MAGIC
• Powered by Visipedia, Merlin Sound ID and Photo ID uses machine learning to identify birds in photos and sounds. Merlin learns to recognize bird species based on training sets of millions of photos and sounds collected by birders at eBird.org, archived in the Macaulay Library at the Cornell Lab of Ornithology.
• Merlin delivers the most accurate results thanks to experienced birders, who curate and annotate sightings, photos, and sounds, who are the true magic behind Merlin.
AMAZING CONTENT
• Merlin has bird photos, songs, and calls, and identification help for anywhere in the world, including Mexico, Costa Rica, South America, Europe, Africa, the Middle East, India, Australia, Korea, Japan, China, and more.
The Cornell Lab of Ornithology’s mission is to interpret and conserve the Earth’s biological diversity through research, education, and citizen science focused on birds and nature. We are able to offer Merlin for free thanks to the generosity of Cornell Lab members, supporters, and citizen-science contributors.