J.P. Morgan Healthcare Conference January 2019

Certain data in this presentation was obtained from various external sources, and neither “iRhythm” or the “Company” nor its affiliates or representatives has verified such data with independent sources. Accordingly, neither the Company nor any of its affiliates, advisers or representatives makes any representations as to the accuracy of that data or undertakes to update such data after the date of this presentation. Such data involves risks and uncertainties and is subject to change based on various factors. The trademarks included herein are the property of the owners and are used for reference purposes only. Such use should not be construed as an endorsement of the products or services of the Company. This presentation and the accompanying oral presentation include forward-looking statements. All statements other than statements of historical facts, including statements regarding our future results of operations and financial position, clinical results, strategy and plans, market size and opportunity, competitive position, industry environment, potential growth opportunities, business model, and our expectations for future operations, are forward-looking statements. We have based these forward-looking statements on our current expectations and projections about future events and trends that we believe may affect our financial condition, results of operations, strategy, short- and long-term business operations and objectives, and financial needs.   These forward-looking statements are subject to a number of risks, uncertainties and assumptions, including those described in “Risk Factors” in our most recent 10-K filed with the SEC on March 31, 2018. Moreover, we operate in a very competitive and rapidly changing environment. New risks emerge from time to time. It is not possible for our management to predict all risks, nor can we assess the impact of all factors on our business or the extent to which any factor, or combination of factors, may cause actual results to differ materially from those contained in any forward-looking statements we may make. In light of these risks, uncertainties and assumptions, the forward-looking events and circumstances discussed in this presentation may not occur and actual results could differ materially and adversely from those anticipated or implied in the forward-looking statements. You should not rely upon forward-looking statements as predictions of future events. Although we believe that the expectations reflected in the forward-looking statements are reasonable, we cannot guarantee that the future results, levels of activity, performance or events and circumstances reflected in the forward-looking statements will be achieved or occur. Moreover, except as required by law, neither we nor any other person assumes responsibility for the accuracy and completeness of the forward-looking statements. We undertake no obligation to update publicly any forward-looking statements for any reason after the date of the prospectus relating to this offering to conform these statements to actual results or to changes in our expectations.   This presentation regarding the Company shall not constitute an offer to sell or the solicitation of an offer to buy any securities, nor shall there be any sale of these securities in any state or jurisdiction in which such offer, solicitation or sale would be unlawful prior to registration or qualification under the securities laws of any such state or jurisdiction. Sales and offers to sell iRhythm securities will only be made in accordance with the Securities Act of 1933, as amended, and applicable SEC regulations, including prospectus requirements. Safe Harbor

Proprietary Data Analytics Patented Wearable Biosensor Clinically-Actionable Digital Report to Inform Diagnosis and Management Clinically Proven and Highly Differentiated Zio Service

Attractive Large Market with Significant TAM Expansion Opportunity … $2B+ Symptomatic Initial Dx (4.5M) High acuity (Zio AT) Low acuity (Zio XT) (Annual U.S. Patients in Millions) Detection Diagnosis Management High Risk Asymptomatic (10+ M) Risk factors: stroke, age, hypertension, heart failure, diabetes, etc. General Population Consumer wearables Ongoing Mgmt (1 M) Post-AF procedures PAF mgmt Event MCT Symptomatic Initial Dx Market (4.5M/year) Holter Source: Frost & Sullivan, AHA 2014 Heart Disease and Stroke Statistics; 2012 Nationwide Inpatient Sample; U.S. Census Bureau; STS database; iRhythm estimates

50% of diagnosed symptomatic arrhythmias occurred beyond 48 hours of monitoring n = 16,142 patients Time Course of Symptomatic Arrhythmia Diagnosis for Zio® Patients % of all patients with symptomatic arrhythmia detected Longer Continuous Monitoring Leads to Better Diagnosis Legacy Holter Monitoring Source: Turakhia, Am J Cardiol, 2013; Tsang, Med Devices: Evidence & Research, 2014; Reiffel, Am J Cardiol, 2005

Zio Proven Superior in Head-to-Head Comparisons % of Patients Diagnosed with Arrhythmia n = 146 patients with both Holter and Zio® patch 66% 42% Source: Barrett, et. al., Comparison of 24-hour Holter Monitoring with 14-Day Novel Adhesive Patch Electrocardiographic Monitoring, Am J Medicine, 2014 72% No Treatment Change 28% Treatment Change n = 74 patients with both Holter and Zio® patch Source: Rosenberg M, Samuel M, Thosani A, and Zimetbaum P Use of a Non Invasive Continuous Monitoring Device in the Management of Atrial Fibrillation. PACE 2012; 00:1–6

Zio Performance On Par with Gold Standard Pacemaker Zio XT AF burden vs. PPM AF burden Nuubo Vest AF burden vs. PPM AF burden “R” Test AF burden vs. PPM AF burden CAM AF burden vs. PPM AF burden Fit Plots for AF Burden Recorded by Pacemaker vs. External Cardiac Monitor Source: Eysenck, et. al., poster presented at European Cardiac Arrhythmia Society meeting, April 2018

Complete Diagnosis Requires Full Characterization of Multiple Arrhythmias Incidence of Atrial Fibrillation Diagnosed With Other Critical Arrhythmias Incidence of First Critical Arrhythmias Detected Beyond 7-Days Source: iRhythm database of ~500,000 consecutive Zio records

High Yield / Low Cost Appeals to Value-Sensitive Payors Source: Commissioned analysis by Decision Drivers Analytics, which used 2015 Medicare fee schedules to estimate Medicare payment and diagnostic yields derived from Giada et al. (2007), Zio® Service Data, Rothman et al. (2007); Tsang et al. (2014) & Reiffel et al. (2005)

TAM Expansion … Access to Previously Untapped High Acuity Segment Drives Greater Zio Adoption Early ZioAT Adoption Experience Benefits of single Zio platform unlock full potential of accounts Account dissatisfaction with current MCT suppliers 60% 40% 16% 70% 14% Zio AT 12/16 12/17 12/18 Illustrative Account Adoption Trend 90% Holter Event & MCT 10% Zio XT

TAM Expansion … Zio’s True AF Burden as a Clinical Tool for Management of AF Patients KP-RHYTHM Study Published in JAMA Cardiology True AF burden measured by Zio in ~2000 paroxysmal AF patients not taking anticoagulation medication 3x increase in stroke risk in paroxysmal AF patients with True AF burden greater than 11% Zio unique in ability to measure True AF burden with 14 days of continuous, uninterrupted data Source: Go, et. al., JAMA Cardiology, May 2018 Thromboembolic Event Rates While Not Taking Anticoagulation

TAM Expansion …Targeted Detection of Silent AF in Asymptomatic Patients Study AF Clinical Cardiology, May 2015 11% New AT / AF diagnosed mSToPS JAMA, July 2018 6.7% New AF diagnosed at 1 year MESA Journal of Electrocardiology, November 2018 4% New Atrial Flutter / AF diagnosed mSToPS New Diagnosis of AF 9x increase in detection of AF with Zio at 4 months 3x increase in detection of AF with Zio at 1 year Publications Utilizing Zio for Detection of Asymptomatic AF Source: Turakhia, Clin Cardiol, 2015; Steinhubl, ACC 2018 Scientific Sessions; Steinhubl, JAMA, 2018; Heckbert, J. Electrocard, 2018

Traditional Approaches to Cardiac Rhythm Classification Have Limitations Challenges in Detecting Irregular Heart Rhythms Traditional approaches learn from limited or intermittent data Computerized arrhythmia interpretation error rates approach 50%1 Traditionally rely on “expert” technicians for correction Lack of suitable training datasets MIT-BIH database (1980) 47 subjects with 4 rhythm classes Most ECG algorithms based on this set Resulting algorithms over fit this dataset and generalize poorly to other data 1 Shah, J Electro Card, 2007 MIT – BIH Arrhythmia Data Base

iRhythm’s deep neural network (DNN) exceeded cardiologist ECG interpretation for all 12 rhythm classes DNN optimization built on a proprietary database of 10+ years and >400 million hours of curated data Improves the accuracy and scalability of ECG analysis, reducing the rate of misinterpretations and inappropriate patient management Manually derived ECG features represent only a fraction of the information …. rendering feature diagnosis a technique of the past Pioneering a New Standard for Cardiac Detection Algorithms Source: Hannun, Nature Medicine, January 2019

Superior Service and Workflow Underlie the Zio Offering Actionable Report Connected Information System Timely Service Delivery Electronic health records integration Bi-directional movement of ordering, eligibility, clinical results, inventory, and billing information Median Delivery Time Wear time 13.8 days Transit: 4.3 days Analysis 1.1 days Source: iRhythm database of ~500,000 consecutive Zio records

The Velocity of Account Penetration Increasing Over Time Average Time for New Accounts to Reach 50+ Zio Rx/Month Months 2013 2014 2015 2016 2017 2018 25+ clinical publications demonstrate superiority of Zio and drive higher brand awareness Reimbursement hurdles largely removed Increased size of salesforce with focus on high potential integrated delivery systems Source: iRhythm internal data and analysis

Sales Expansion Fueling Growth Rapid Expansion of Sales Headcount to Continue into 2019 Number of Sales Representatives Rep Productivity Continues to Increase Average Annual Sales/Rep by Tenure $M Source: iRhythm internal data and analysis

Track Record of Sustained High Financial Performance Revenue Net income/Loss * As of September 2018 2014 2015 2016 2017 2018 est.* 51% 59% 67% 72% 73.5 -74.5% GM% 60% CAGR Revenue $M