Background: Lipid discordance, characterized by conflicting results among various lipid measures used in cardiovascular risk assessment, has been a subject of interest and concern. Previous comparisons of LDL-C and non-HDL-C with ApoB and LDL particle numbers as cardiovascular risk predictors have shown conflicting results, partly because they were treated as independent variables. This study aimed to examine the extent of lipid discordance and its implications for risk assessment. Methods: A cross-sectional study involving 106 individuals with lipid panels was conducted, and LDL cholesterol (LDL-C), non-HDL cholesterol (non-HDL-C), LDL particle number (LDL-P), and Apolipoprotein B (ApoB) were measured using standardized methods. Lipid discordance was defined as disagreement in risk categorization between different measures based on established cut-off values. Prior studies have described three different approaches to identify discordance such as quintiles, percentiles or the median, and all have demonstrated similar clinical results. Our analysis utilized the percentile method. Results: The results revealed a substantial level of lipid discordance, with 91.5% of individuals having at least one discordance among the four lipid measures. Most prevalent was the discordance between LDL-C and LDL-P, observed in 70.75% of individuals, with an average discordance of approximately 45.03% for LDL-P. Additionally, 20.75% of individuals displayed discordance between LDL-C and ApoB, averaging about 17.07%. The remaining 8.49% showed relative concordance. Conclusion: Our study highlights significant lipid discordance among various measures, impacting cardiovascular risk assessment. Increased ApoB or LDL particle numbers elevate risk, even with stable LDL-C and non-HDL-C. Conversely, low ApoB or LDL particles and elevated LDL-C or non-HDL-C indicate lower risk. We stress the limitations of population-based lipid management and advocate personalized strategies based on the most discordant lipid measure, improving accuracy and outcomes. Individualized risk assessment and tailored interventions are crucial.