Mettler Toledo International (MTD) EBITDA (2009 - 2026)
Mettler Toledo International (MTD) reported EBITDA of $361.17 million for Q2 2026, up 16.4% from $310.19 million a year earlier and up 32.9% from the prior quarter.
Powered by 
Analysis
Mettler Toledo International (MTD) EBITDA (2009 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Mettler Toledo International's EBITDA came in at $1.36 billion, up 6.4% year-over-year; for FY2025, it was $1.3 billion, down 0.2% from FY2024.
- EBITDA has a five-year compound annual growth rate of 7.0% (FY2020 to FY2025).
- By year, EBITDA came in at $1.3 billion in FY2024 (+5.1%), $1.24 billion in FY2023 (-4.3%), $1.3 billion in FY2022 (+11.7%) and $1.16 billion in FY2021 (+24.9%).
- Five-year quarterly EBITDA spans a low of $262.62 million in Q1 2025 and a high of $391.2 million in Q4 2025.
- Year over year, EBITDA has now increased in each of the last five quarters, with growth averaging 5.8% over the last eight quarters.
- The high point for year-over-year EBITDA in five years was Q4 2024 (growth of 27.2%); the low point was Q4 2023 (a decline of 22.3%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $271.72 million (Q1 2026), $391.2 million (Q4 2025) and $336.69 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Caterpillar | 367.91 Bn | 339.61 Bn | 7.76 Bn | 4.91 Bn |
| 2 | Amphenol | 215.11 Bn | 209.81 Bn | 3.55 Bn | 2.93 Bn |
| 3 | Deere | 167.41 Bn | 176.17 Bn | 4.66 Bn | 2.46 Bn |
| 4 | Eaton | 166.85 Bn | 164.08 Bn | 2.86 Bn | 1.79 Bn |
| 5 | Parker-Hannifin | 121.33 Bn | 119.46 Bn | 2.25 Bn | 1.61 Bn |
| 6 | Vertiv Holdings | 93.43 Bn | 84.05 Bn | 1.23 Bn | 754.30 Mn |
| 7 | Emerson Electric | 90.26 Bn | 83.02 Bn | 2.66 Bn | 1.69 Bn |
| 8 | 3M | 82.47 Bn | 63.93 Bn | 2.68 Bn | 1.32 Bn |
| 9 | Illinois Tool Works | 75.21 Bn | 71.77 Bn | 1.90 Bn | 1.25 Bn |
| 10 | Mettler Toledo International | 33.63 Bn | 33.39 Bn | 650.22 Mn | 361.17 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 361.17 Mn |
| Mar 31, 2026 | 271.72 Mn |
| Dec 31, 2025 | 391.20 Mn |
| Sep 30, 2025 | 336.69 Mn |
| Jun 30, 2025 | 310.19 Mn |
| Mar 31, 2025 | 262.62 Mn |
| Dec 31, 2024 | 380.64 Mn |
| Sep 30, 2024 | 325.02 Mn |
| Jun 30, 2024 | 309.30 Mn |
| Mar 31, 2024 | 288.41 Mn |
| Dec 31, 2023 | 299.34 Mn |
| Sep 30, 2023 | 319.08 Mn |
| Jun 30, 2023 | 329.92 Mn |
| Mar 31, 2023 | 291.98 Mn |
| Dec 31, 2022 | 385.18 Mn |
| Sep 30, 2022 | 333.55 Mn |
| Jun 30, 2022 | 311.47 Mn |
| Mar 31, 2022 | 265.72 Mn |
| Dec 31, 2021 | 345.03 Mn |
| Sep 30, 2021 | 299.38 Mn |
API Access
Mettler Toledo International 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=MTD&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "MTD", "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=MTD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();