Wendy's (WEN) EBITDA (2009 - 2026)
Wendy's (WEN) recorded EBITDA of $121.92 million in Q2 2026, down 16.1% from $145.31 million a year earlier but up 10.6% from the prior quarter.
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Analysis
Wendy's (WEN) EBITDA (2009 - 2026) Analysis & Trends
On a TTM basis, Wendy's' EBITDA came in at $477.35 million as of Jun 28, 2026, down 11.2% year-over-year; for FY2025, it came in at $514.32 million, down 2.8% from FY2024.
- Annual EBITDA has a four-year compound annual growth rate of 6.3% (FY2021 to FY2025).
- Across earlier years, EBITDA came in at $529.29 million in FY2024 (-0.2%), $530.55 million in FY2023 (+8.5%), $489.12 million in FY2022 and $402.08 million in FY2021.
- Quarterly EBITDA has ranged from $105.82 million in Q4 2022 to $145.31 million in Q2 2025 over the past five years.
- On a year-over-year basis, EBITDA has declined for three consecutive quarters, with an average decline of 4.5% over the last eight quarters.
- Peak year-over-year performance for EBITDA in the last five years was growth of 19.3% in Q4 2023, against a decline of 17.9% in Q4 2025 at the low end.
- Per Business Quant, the preceding three quarters came in at $110.26 million (Q1 2026), $109.51 million (Q4 2025) and $135.67 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 165.31 Bn | 160.13 Bn | 6.42 Bn | 3.90 Bn |
| 2 | Starbucks | 108.61 Bn | 96.24 Bn | - | 1.37 Bn |
| 3 | Chipotle Mexican Grill | 40.32 Bn | 36.30 Bn | - | 623.92 Mn |
| 4 | Yum Brands | 37.73 Bn | 34.61 Bn | 1.47 Bn | 715.00 Mn |
| 5 | Restaurant Brands International | 24.95 Bn | 22.05 Bn | 1.38 Bn | 793.00 Mn |
| 6 | Darden Restaurants | 22.46 Bn | 21.57 Bn | -113.70 Mn | 663.10 Mn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | 793.00 Mn |
| 8 | Yum China Holdings | 14.17 Bn | 8.53 Bn | 537.00 Mn | 468.00 Mn |
| 9 | Texas Roadhouse | 10.39 Bn | 9.75 Bn | - | 201.13 Mn |
| 10 | Wendy's | 1.22 Bn | -14.01 Mn | 363.30 Mn | 121.92 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 28, 2026 | 121.92 Mn |
| Mar 29, 2026 | 110.26 Mn |
| Dec 28, 2025 | 109.51 Mn |
| Sep 28, 2025 | 135.67 Mn |
| Jun 29, 2025 | 145.31 Mn |
| Mar 30, 2025 | 123.84 Mn |
| Dec 29, 2024 | 133.31 Mn |
| Sep 29, 2024 | 135.25 Mn |
| Jun 30, 2024 | 140.52 Mn |
| Mar 31, 2024 | 120.22 Mn |
| Dec 31, 2023 | 126.25 Mn |
| Oct 1, 2023 | 139.74 Mn |
| Jul 2, 2023 | 145.04 Mn |
| Apr 2, 2023 | 119.53 Mn |
| Jan 1, 2023 | 105.82 Mn |
| Oct 2, 2022 | 133.28 Mn |
| Jul 3, 2022 | 129.71 Mn |
| Apr 3, 2022 | 108.11 Mn |
| Oct 3, 2021 | 111.14 Mn |
| Jul 4, 2021 | 157.51 Mn |
API Access
Wendy's EBITDA API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=ebitda&ticker=WEN&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "WEN", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=ebitda&ticker=WEN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();