One of the main causes of the high mortality rate in lung cancer is the late-stage tumor detection. Early diagnosis is therefore essential to increase the chances of obtaining an effective treatment quickly thus increasing the survival rate. Current screening techniques are based on imaging, with low-dose computed tomography (LDCT) as the pivotal approach. Even if LDCT has high accuracy, its invasiveness and high false positive rate limit its application to high-risk population screening. A non-invasive, cost-efficient, and easy-to-use test should instead be designed as an alternative. Exhaled breath contains thousands of volatile organic compounds (VOCs). Since ancient times, it has been understood that changes in the VOCs' mixture may be directly related to the presence of a disease, and recent studies have quantified the change in the compounds' concentration. Analyzing exhaled breath to achieve lung cancer early diagnosis represents a non-invasive, low-cost, and user-friendly approach, thus being a promising candidate for high-risk lung cancer population screening. This review discusses technological solutions that have been proposed in the literature as tools to analyze exhaled breath for lung cancer diagnosis, together with factors that potentially affect the outcome of the analysis. Even if research on this topic started many years ago, and many different technological approaches have since been adopted, there is still no validated clinical application of this technique. Standard guidelines and protocols should be defined by the medical community in order to translate exhaled breath analysis to clinical practice.