Edwards Lifesciences (EW) EBITDA (2009 - 2026)
Edwards Lifesciences (EW) posted EBITDA of $344 million for Q3 2026, down 0.7% from $346.3 million a year earlier and down 38.1% from the prior quarter.
Edwards Lifesciences (EW) EBITDA (2009 - 2026) Analysis & Trends
For the trailing twelve months through Sep 30, 2026, EBITDA at Edwards Lifesciences was $1.61 billion, up 1.9% year-over-year; for FY2025, it was $1.42 billion, down 7.4% from FY2024.
- Annual EBITDA shows a five-year compound annual growth rate of 7.2% (FY2020 to FY2025).
- In prior years, Edwards Lifesciences' EBITDA was $1.53 billion in FY2024 (+5.5%), $1.45 billion in FY2023 (-11.2%), $1.64 billion in FY2022 (-10.3%) and $1.83 billion in FY2021 (+81.6%).
- Quarterly EBITDA has run from a low of $193.8 million in Q4 2025 to a high of $555.9 million in Q2 2026 over five years.
- On a year-over-year basis, EBITDA increased in four of the last eight quarters, with growth averaging 0.3%.
- The strongest year-over-year quarter for EBITDA in the past five years was Q4 2023, with growth of 64.5%; the weakest was Q4 2025, with a decline of 45.4%.
- According to Business Quant data, EBITDA for the three prior quarters was $555.9 million (Q2 2026), $518.5 million (Q1 2026) and $193.8 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 262.96 Bn | 239.47 Bn | 5.13 Bn | 3.09 Bn |
| 2 | Abbott Laboratories | 191.48 Bn | 165.35 Bn | 7.39 Bn | 2.61 Bn |
| 3 | Danaher | 164.52 Bn | 144.17 Bn | 3.84 Bn | 1.97 Bn |
| 4 | Intuitive Surgical | 161.08 Bn | 141.37 Bn | 2.08 Bn | 789.70 Mn |
| 5 | Medtronic | 132.40 Bn | 97.65 Bn | 6.34 Bn | 2.49 Bn |
| 6 | Stryker | 125.58 Bn | 111.77 Bn | 4.25 Bn | 1.33 Bn |
| 7 | Boston Scientific | 64.00 Bn | 59.43 Bn | 3.43 Bn | 1.19 Bn |
| 8 | Edwards Lifesciences | 60.27 Bn | 43.47 Bn | 1.35 Bn | 344.00 Mn |
| 9 | Becton Dickinson | 59.29 Bn | 56.44 Bn | 2.32 Bn | 1.23 Bn |
| 10 | Agilent Technologies | 50.39 Bn | 43.28 Bn | 1.04 Bn | 510.00 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 344.00 Mn |
| Jun 30, 2026 | 555.90 Mn |
| Mar 31, 2026 | 518.50 Mn |
| Dec 31, 2025 | 193.80 Mn |
| Sep 30, 2025 | 346.30 Mn |
| Jun 30, 2025 | 449.30 Mn |
| Mar 31, 2025 | 431.40 Mn |
| Dec 31, 2024 | 355.20 Mn |
| Sep 30, 2024 | 385.10 Mn |
| Jun 30, 2024 | 406.10 Mn |
| Mar 31, 2024 | 387.50 Mn |
| Dec 31, 2023 | 383.50 Mn |
| Sep 30, 2023 | 402.80 Mn |
| Jun 30, 2023 | 299.60 Mn |
| Mar 31, 2023 | 423.60 Mn |
| Dec 31, 2022 | 233.10 Mn |
| Sep 30, 2022 | 437.80 Mn |
| Jun 30, 2022 | 493.60 Mn |
| Mar 31, 2022 | 473.50 Mn |
| Dec 31, 2021 | 407.40 Mn |
Edwards Lifesciences 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=EW&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "EW", "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=EW&period=max&api_key=YOUR_API_KEY");
const data = await res.json();