Autism spectrum disorder (ASD) trends have been gaining a great deal of focus in recent decades, as many studies worldwide show a continued rise in incidence rates. Many researchers have begun analyzing socioeconomic data in relation to ASD in an effort to understand the source of these changing rates and the role of awareness and access to resources. In this study, we aim to contribute to this body of knowledge by examining incidence time trends of ASD in Israel according to socioeconomic factors. While similar studies have been conducted in Israel, this study is the first of its kind to include the total population. Individual‐level data from the Israeli National Insurance Institute were used to determine cumulative incidence of ASD, first for the total population, and then stratified by population group and income categories. Multivariable logistic regression models were fit to analyze associations between income category and both risk of ASD and risk of ASD diagnosis in later age. A total of 431,348 children were examined in this study, with 13,841 cases of ASD. The cumulative incidence of all children aged 8 in 2015 was 0.64%, marking an increase compared to previous literature from Israel. Within our study period, ASD incidence followed this increase until the 2009 birth cohort, where it began to stabilize. Our initial findings from regression models showed strong positive associations between household income and ASD incidence, as expected. After factoring in population group, however, the elevated ASD incidence rates in the highest income bracket decreased. Autism Res 2019, 12: 1870–1879. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. Lay Summary This study contributes comprehensive and current data on ASD trends overtime in Israel and introduces crucial insights regarding the impact of socioeconomic factors on ASD diagnoses. We found a rise in ASD that began leveling off in 2009. We identified more ASD diagnoses occurring in families with higher incomes and in the General Population, pointing to the important role of sociodemographic factors on ASD diagnoses.