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P4P Legify: Leg workout

P4P Legify: Leg workout

Passion4Profession Inc.

Health & Fitness免费v7.0.4
App Store
评分

3.9

19 条评分

星级

★★★★☆

最近更新

2026年3月12日

发布日期

2014年6月29日

更新内容

v7.0.4

Fixed a bug where purchase restoration failed in some cases.

应用信息

开发者
Passion4Profession Inc.
分类
Health & Fitness
价格
免费
版本
7.0.4
App ID
887893349

简介

Want stronger legs without guesswork? Legify helps you train your legs at home or at the gym with guided, progressive workouts you can follow instantly. From the creators of the famous P4P YouTube workouts (hundreds of millions of views): the same pro quality, rebuilt for 2026. WHY LEGIFY IN 2026? ► AI COACH In 3 taps, the AI Coach suggests a plan that matches your level. Not a static routine—real progression. ► 2026 UPDATE: P4P SUITE INCLUDED One subscription now unlocks VIP access to ALL 7 primary Passion4Profession apps: Abify, Chestify, Buttify, Legify, Burnify, Quickify and more. Pay for 1, get 7. ► PRO WORKOUTS HD videos, iconic P4P 3D animations, clear guidance. Train quads, hamstrings, calves and thighs. ► P4P MUSIC High-energy original tracks to keep your rhythm, or use your own music. Download Legify and start today. UNLOCK ALL THE FEATURES You can sign up to a monthly subscription in order to unlock the app and utilise its full potential. Payment will be charged to your iTunes Account at confirmation of purchase. Subscription will automatically renew​ unless auto-renew is turned off at least 24-hours before the end of the current period and cancellation of the current active subscription period is not allowed. Account will be charged for renewal within 24-hours prior to the end of the current period. Auto-renewal can be turned off in your Account Settings in iTunes after purchase. Any unused portion of the free trial period, will be forfeited when you purchases a monthly subscription to the app. Terms of use: http://passion4profession.net/home#terms-of-use

下载量预测

专业 · 预览

预估总下载量

2K1K3K
保守估计乐观估计

9

低 / 月

12

预估 / 月

19

高 / 月

基于19 条评分
假设评分率1.1%
应用年龄145 个月

基于评分数量 ÷ 类别评分率估算,实际下载量误差可达 ±50%,与 Sensor Tower 方法一致。