Doll Run: Fashion Dress Up
Action

Doll Run: Fashion Dress Up

1.4 · 84.78MB

↓ Download for Android
Version1.4
Size84.78MB
CategoryAction

Screenshots

Screenshots

About this app

Doll Run: Fashion Dress Up is an exciting dress-up runner game. With tons of gorgeous outfits, you can create your own perfect doll look. Players will collect fashionable outfits and race to the finish line on challenging tracks. If you love dress-up games, fashion makeovers, and exciting runners, then Doll Run: Fashion Dress Up is the perfect game for you! Join this fashion extravaganza, unlock stunning looks, and become a true runway queen!

Features:

Fashion-themed running game for girls!

Huge variety of outfits, shoes, and accessories to collect.

Style your character for different challenges and dress codes.

Strike a pose on the catwalk and earn style points.

Easy to play, hard to master fashion runner gameplay.

Regular updates with new clothes and style events!

Playing Tips:

Collect as many fashionable items as possible to unlock stunning looks for your doll

Pay attention to the theme of the challenge and choose the outfit that best fits it

Practice your runway poses to earn style points and impress the crowd

Conclusion:

Doll Run: Fashion Dress Up is the perfect combination of fashion, fun, and competition. With a wide range of outfits to collect, challenges to overcome, and regular updates to keep things exciting, this game is sure to keep you entertained for hours. Download now and start your stylish journey to become the ultimate runway queen!

More information

Updated on source
2025-09-10
Size
84.78MB
Version
1.4
Requirements
Android
Popularity
536

App2U App Overview

Doll Run: Fashion Dress Up is listed on App2U as an Android game in the Action category. The version recorded here is 1.4. The listed package size is 84.78MB.

For this category, useful points of comparison include combat style, control responsiveness requirements and level structure. These are areas to check in the app description and publisher information, rather than features to assume from the category alone. Giving priority to the aspects you expect to use most often makes comparisons with similar listings more relevant.

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